Workflow

The data pipeline for the delta farm project was starting to become convoluted. It felt prudent to outline it somewhere so i decided to give it a shot in Rmarkdown. ;) Thanks Andrew.
The work consists of four principal steps.

  • Read In
  • Quality Assurance
  • Visualization
  • Analysis

The later steps may well be beyond the scope of this document. As such, i will reserve those for a later date.
First we will call on our libraries to carry out subsequent functions.

library(lubridate)
library(tidyverse)
library(ggpubr)
library(zoo)
library(scales)
library(gridExtra)
library(grid)
library(mosaic)
library(knitr)
library(kableExtra)
library(mice)
library(patchwork)

Now we are ready to read in our data set which is stored as a csv. This data set includes, inbedded in it, the QAQC checks carried out for sample analysis as well as sampling trip quality objectives outlined in the project QAPP.

1 Read In

So, lets give that csv a look.

dat <- read.csv("DF_final.csv",
                stringsAsFactors = FALSE,
                na.strings = c("", "NA") 
) %>% 
mutate( 
    Date = lubridate::mdy(Date),
    sampleid = as.factor(sampleid),
    farm = as.factor(farm),
    treatment = as.factor(treatment),
    TUR_ntu = as.numeric(TUR_ntu),      
    sample_type = as.factor(sample_type)
  )

We pipe the data set to mutate so R will be sure to read the variables like we want them. This is the first touch of housekeeping.
Now that we have a dataframe, what does it look like?

str(dat)
## 'data.frame':    488 obs. of  43 variables:
##  $ Date               : Date, format: "2018-02-05" "2018-02-05" ...
##  $ qaqc.check         : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ sampleid           : Factor w/ 24 levels "ARR1","ARR2",..: 10 11 21 22 10 11 19 20 21 22 ...
##  $ sample_type        : Factor w/ 2 levels "EOF","INST": 1 1 1 1 1 1 1 1 1 1 ...
##  $ farm               : Factor w/ 11 levels "ARR","CAR","DCDC",..: 5 5 10 10 5 5 9 9 10 10 ...
##  $ treatment          : Factor w/ 2 levels "CCMT","FBM": 1 2 1 2 1 2 1 2 1 2 ...
##  $ initialweight_g    : num  0.0796 0.0948 0.1057 0.0985 0.0845 ...
##  $ filtered_volume_ml : int  20 50 20 20 20 20 20 20 20 20 ...
##  $ final_weight_g     : num  0.105 0.112 0.104 0.11 0.101 ...
##  $ TSS_mgl            : num  1285 340 -105 555 800 ...
##  $ TUR_ntu            : num  221 302 223 434 576 2250 919 1420 1060 2370 ...
##  $ tur.std.check      : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ NO3.NO2_mgl        : num  0.891 5.59 0.759 5.47 1.4 4.97 1.8 2.94 1.56 5.61 ...
##  $ TKN_mgl            : num  1.51 0 1.85 1.01 1.08 1.1 2.43 3 0.98 0 ...
##  $ TN_mgl             : num  2.4 5.5 2.6 6.48 2.47 6.07 4.23 5.94 2.54 5.23 ...
##  $ tn.std.check       : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ TIP_mgl            : num  3.03 3.06 2.05 2.65 1.85 3.14 4.15 5.03 1.72 2.31 ...
##  $ tip.std.check      : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ NH3_mgl            : num  0.0508 -0.0208 -0.0445 0.0758 0.0655 0.0581 0.0116 0.0352 0.0903 0.0847 ...
##  $ nh3.std.check      : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ OrthoP_mgl         : num  0.205 0.115 0.00211 0.00481 0.191 0.192 0.396 0.653 0.192 0.22 ...
##  $ orthop.std.check   : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ NOx_mgl            : num  0.287 4.71 0.0272 4.65 0.416 1.42 0.121 0.551 0.17 2.55 ...
##  $ nox.std.check      : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
##  $ NO2_mgl            : num  -0.0314 -0.0257 -0.0369 -0.0342 -0.037 -0.0395 -0.0312 -0.0308 -0.0334 -0.0364 ...
##  $ no2.std.check      : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ NO3_mgl            : num  0.262 4.685 0.0022 4.625 0.391 ...
##  $ event_disch_l      : num  746149 141626 200606 345867 1901124 ...
##  $ acft_discharge     : num  0.605 0.115 0.163 0.28 1.542 ...
##  $ in_runoff_ac       : num  0.3813 0.0845 0.1366 0.1913 0.9715 ...
##  $ TSS_kg             : num  958.8 48.2 -21.1 192 1520.9 ...
##  $ TN_kg              : num  1.791 0.779 0.522 2.241 4.696 ...
##  $ TIP_kg             : num  2.261 0.433 0.411 0.917 3.517 ...
##  $ TSS_lb             : num  2113.8 106.2 -46.4 423.2 3353 ...
##  $ TN_lb              : num  3.95 1.72 1.15 4.94 10.35 ...
##  $ TIP_lb             : num  4.984 0.955 0.907 2.021 7.754 ...
##  $ TSS_lbac           : num  111.02 6.58 -3.25 24.06 176.1 ...
##  $ TN_lbac            : num  0.2073 0.1065 0.0805 0.2809 0.5437 ...
##  $ TIP_lbac           : num  0.2618 0.0592 0.0634 0.1149 0.4072 ...
##  $ dissolvedO2_mg_l   : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ dissolvedO2_sat_per: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ turbidity_sonde_ntu: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ watertemp_c        : num  NA NA NA NA NA NA NA NA NA NA ...

Here we can see all the variables in the dataset. Though, we can see that they don’t seem to single style pattern. Lets fix that with a bit of code that will switch all the underscores to periods.

names(dat) <- gsub(
  x = names(dat), 
  pattern = "\\_", 
  replacement = "."
)

Again, lets take a look at the structure just to make sure it’s what we want.

str(dat)
## 'data.frame':    488 obs. of  43 variables:
##  $ Date               : Date, format: "2018-02-05" "2018-02-05" ...
##  $ qaqc.check         : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ sampleid           : Factor w/ 24 levels "ARR1","ARR2",..: 10 11 21 22 10 11 19 20 21 22 ...
##  $ sample.type        : Factor w/ 2 levels "EOF","INST": 1 1 1 1 1 1 1 1 1 1 ...
##  $ farm               : Factor w/ 11 levels "ARR","CAR","DCDC",..: 5 5 10 10 5 5 9 9 10 10 ...
##  $ treatment          : Factor w/ 2 levels "CCMT","FBM": 1 2 1 2 1 2 1 2 1 2 ...
##  $ initialweight.g    : num  0.0796 0.0948 0.1057 0.0985 0.0845 ...
##  $ filtered.volume.ml : int  20 50 20 20 20 20 20 20 20 20 ...
##  $ final.weight.g     : num  0.105 0.112 0.104 0.11 0.101 ...
##  $ TSS.mgl            : num  1285 340 -105 555 800 ...
##  $ TUR.ntu            : num  221 302 223 434 576 2250 919 1420 1060 2370 ...
##  $ tur.std.check      : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ NO3.NO2.mgl        : num  0.891 5.59 0.759 5.47 1.4 4.97 1.8 2.94 1.56 5.61 ...
##  $ TKN.mgl            : num  1.51 0 1.85 1.01 1.08 1.1 2.43 3 0.98 0 ...
##  $ TN.mgl             : num  2.4 5.5 2.6 6.48 2.47 6.07 4.23 5.94 2.54 5.23 ...
##  $ tn.std.check       : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ TIP.mgl            : num  3.03 3.06 2.05 2.65 1.85 3.14 4.15 5.03 1.72 2.31 ...
##  $ tip.std.check      : logi  FALSE FALSE FALSE FALSE TRUE TRUE ...
##  $ NH3.mgl            : num  0.0508 -0.0208 -0.0445 0.0758 0.0655 0.0581 0.0116 0.0352 0.0903 0.0847 ...
##  $ nh3.std.check      : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ OrthoP.mgl         : num  0.205 0.115 0.00211 0.00481 0.191 0.192 0.396 0.653 0.192 0.22 ...
##  $ orthop.std.check   : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ NOx.mgl            : num  0.287 4.71 0.0272 4.65 0.416 1.42 0.121 0.551 0.17 2.55 ...
##  $ nox.std.check      : logi  FALSE FALSE FALSE FALSE FALSE FALSE ...
##  $ NO2.mgl            : num  -0.0314 -0.0257 -0.0369 -0.0342 -0.037 -0.0395 -0.0312 -0.0308 -0.0334 -0.0364 ...
##  $ no2.std.check      : logi  TRUE TRUE TRUE TRUE TRUE TRUE ...
##  $ NO3.mgl            : num  0.262 4.685 0.0022 4.625 0.391 ...
##  $ event.disch.l      : num  746149 141626 200606 345867 1901124 ...
##  $ acft.discharge     : num  0.605 0.115 0.163 0.28 1.542 ...
##  $ in.runoff.ac       : num  0.3813 0.0845 0.1366 0.1913 0.9715 ...
##  $ TSS.kg             : num  958.8 48.2 -21.1 192 1520.9 ...
##  $ TN.kg              : num  1.791 0.779 0.522 2.241 4.696 ...
##  $ TIP.kg             : num  2.261 0.433 0.411 0.917 3.517 ...
##  $ TSS.lb             : num  2113.8 106.2 -46.4 423.2 3353 ...
##  $ TN.lb              : num  3.95 1.72 1.15 4.94 10.35 ...
##  $ TIP.lb             : num  4.984 0.955 0.907 2.021 7.754 ...
##  $ TSS.lbac           : num  111.02 6.58 -3.25 24.06 176.1 ...
##  $ TN.lbac            : num  0.2073 0.1065 0.0805 0.2809 0.5437 ...
##  $ TIP.lbac           : num  0.2618 0.0592 0.0634 0.1149 0.4072 ...
##  $ dissolvedO2.mg.l   : num  NA NA NA NA NA NA NA NA NA NA ...
##  $ dissolvedO2.sat.per: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ turbidity.sonde.ntu: num  NA NA NA NA NA NA NA NA NA NA ...
##  $ watertemp.c        : num  NA NA NA NA NA NA NA NA NA NA ...

Later we will want to consider our data from a seasonal perspective given the nature of the treatment. Lets go ahead and add this variable to the data frame. I’ll assign the season with an if~else statement then tidy up so R will undertand this factor in our analysis.

dat$season <- ifelse(
  month(dat$Date) == 11 | month(dat$Date) ==  12 | month(dat$Date) == 1| 
    month(dat$Date) == 2 |  month(dat$Date) == 3 | month(dat$Date) == 4,
  "cover",
  "cash")

dat <- dat %>% 
  mutate(season = as.factor(season))

One last thing before we move on. With a scollable box we should be able to preview our dataframe.

kable(dat, "html", digits = 4) %>% 
  kable_paper() %>% 
  scroll_box(height = "600px")
Date qaqc.check sampleid sample.type farm treatment initialweight.g filtered.volume.ml final.weight.g TSS.mgl TUR.ntu tur.std.check NO3.NO2.mgl TKN.mgl TN.mgl tn.std.check TIP.mgl tip.std.check NH3.mgl nh3.std.check OrthoP.mgl orthop.std.check NOx.mgl nox.std.check NO2.mgl no2.std.check NO3.mgl event.disch.l acft.discharge in.runoff.ac TSS.kg TN.kg TIP.kg TSS.lb TN.lb TIP.lb TSS.lbac TN.lbac TIP.lbac dissolvedO2.mg.l dissolvedO2.sat.per turbidity.sonde.ntu watertemp.c season
2018-02-05 FALSE MUR1 EOF MUR CCMT 0.0796 20 0.1053 1285.0 221.00 FALSE 0.8910 1.5100 2.400 FALSE 3.030 FALSE 0.0508 TRUE 0.2050 TRUE 0.2870 FALSE -0.0314 TRUE 0.2620 746149.200 0.6050 0.3813 958.8017 1.7908 2.2608 2113.7743 3.9479 4.9842 111.0176 0.2073 0.2618 NA NA NA NA cover
2018-02-05 FALSE MUR2 EOF MUR FBM 0.0948 50 0.1118 340.0 302.00 FALSE 5.5900 0.0000 5.500 FALSE 3.060 FALSE -0.0208 TRUE 0.1150 TRUE 4.7100 FALSE -0.0257 TRUE 4.6850 141626.200 0.1148 0.0845 48.1529 0.7789 0.4334 106.1579 1.7173 0.9554 6.5814 0.1065 0.0592 NA NA NA NA cover
2018-02-05 FALSE SIM1 EOF SIM CCMT 0.1057 20 0.1036 -105.0 223.00 FALSE 0.7590 1.8500 2.600 FALSE 2.050 FALSE -0.0445 TRUE 0.0021 TRUE 0.0272 FALSE -0.0369 TRUE 0.0022 200605.800 0.1627 0.1366 -21.0636 0.5216 0.4112 -46.4368 1.1499 0.9066 -3.2496 0.0805 0.0634 NA NA NA NA cover
2018-02-05 FALSE SIM2 EOF SIM FBM 0.0985 20 0.1096 555.0 434.00 FALSE 5.4700 1.0100 6.480 FALSE 2.650 FALSE 0.0758 TRUE 0.0048 TRUE 4.6500 FALSE -0.0342 TRUE 4.6250 345866.700 0.2804 0.1913 191.9560 2.2412 0.9165 423.1862 4.9410 2.0206 24.0583 0.2809 0.1149 NA NA NA NA cover
2018-02-07 TRUE MUR1 EOF MUR CCMT 0.0845 20 0.1005 800.0 576.00 TRUE 1.4000 1.0800 2.470 TRUE 1.850 TRUE 0.0655 TRUE 0.1910 TRUE 0.4160 FALSE -0.0370 TRUE 0.3910 1901124.000 1.5415 0.9715 1520.8992 4.6958 3.5171 3352.9744 10.3523 7.7538 176.1016 0.5437 0.4072 NA NA NA NA cover
2018-02-07 TRUE MUR2 EOF MUR FBM 0.1092 20 0.1157 325.0 2250.00 TRUE 4.9700 1.1000 6.070 TRUE 3.140 TRUE 0.0581 TRUE 0.1920 TRUE 1.4200 FALSE -0.0395 TRUE 1.3950 5352589.000 4.3401 3.1932 1739.5914 32.4902 16.8071 3835.1033 71.6279 37.0530 237.7621 4.4407 2.2971 NA NA NA NA cover
2018-02-07 TRUE SCH1 EOF SCH CCMT 0.0785 20 0.1130 1725.0 919.00 TRUE 1.8000 2.4300 4.230 TRUE 4.150 TRUE 0.0116 TRUE 0.3960 TRUE 0.1210 FALSE -0.0312 TRUE 0.0960 1279235.000 1.0373 1.1991 2206.6804 5.4112 5.3088 4864.8476 11.9295 11.7038 468.6751 1.1493 1.1275 NA NA NA NA cover
2018-02-07 TRUE SCH2 EOF SCH FBM 0.1054 20 0.1209 775.0 1420.00 TRUE 2.9400 3.0000 5.940 TRUE 5.030 TRUE 0.0352 TRUE 0.6530 TRUE 0.5510 FALSE -0.0308 TRUE 0.5260 1532954.000 1.2430 1.6355 1188.0394 9.1057 7.7108 2619.1516 20.0745 16.9991 287.1877 2.2012 1.8639 NA NA NA NA cover
2018-02-07 TRUE SIM1 EOF SIM CCMT 0.0808 20 0.1226 2090.0 1060.00 TRUE 1.5600 0.9800 2.540 TRUE 1.720 TRUE 0.0903 TRUE 0.1920 TRUE 0.1700 FALSE -0.0334 TRUE 0.1450 67448.230 0.0547 0.0459 140.9668 0.1713 0.1160 310.7754 0.3777 0.2558 21.7478 0.0264 0.0179 NA NA NA NA cover
2018-02-07 TRUE SIM2 EOF SIM FBM 0.0949 20 0.1165 1080.0 2370.00 TRUE 5.6100 0.0000 5.230 FALSE 2.310 TRUE 0.0847 TRUE 0.2200 TRUE 2.5500 FALSE -0.0364 TRUE 2.5250 1620000.000 1.3136 0.8961 1749.6000 8.4726 3.7422 3857.1682 18.6787 8.2501 219.2819 1.0619 0.4690 NA NA NA NA cover
2018-02-12 TRUE MUR1 EOF MUR CCMT 0.0930 50 0.1164 468.0 189.00 TRUE 1.0100 1.5600 2.570 FALSE 1.490 TRUE 0.0318 TRUE 0.1530 TRUE 0.4980 FALSE -0.0328 TRUE 0.4730 983345.300 0.7973 0.5025 460.2056 2.5272 1.4652 1014.5693 5.5715 3.2301 53.2862 0.2926 0.1697 NA NA NA NA cover
2018-02-12 TRUE MUR2 EOF MUR FBM 0.0962 50 0.1248 572.0 163.00 TRUE 3.3100 0.6080 3.920 FALSE 1.370 TRUE 0.0741 TRUE 0.1270 TRUE 2.6600 FALSE -0.0291 TRUE 2.6350 613716.500 0.4976 0.3661 351.0458 2.4058 0.8408 773.9157 5.3038 1.8536 47.9799 0.3288 0.1149 NA NA NA NA cover
2018-02-12 TRUE SIM1 EOF SIM CCMT 0.0933 50 0.1135 404.0 106.00 TRUE 0.5250 0.9110 1.440 FALSE 1.040 TRUE 0.1240 TRUE 0.0319 TRUE 0.2110 FALSE -0.0326 TRUE 0.1860 811739.000 0.6582 0.5527 327.9426 1.1689 0.8442 722.9822 2.5770 1.8611 50.5936 0.1803 0.1302 NA NA NA NA cover
2018-02-12 TRUE SIM2 EOF SIM FBM 0.1100 50 0.1338 476.0 130.00 TRUE 2.2700 0.5780 2.850 FALSE 1.550 TRUE 0.0661 TRUE 0.0241 TRUE 1.7900 FALSE -0.0329 TRUE 1.7650 3432976.000 2.7836 1.8990 1634.0966 9.7840 5.3211 3602.5293 21.5698 11.7309 204.8055 1.2263 0.6669 NA NA NA NA cover
2018-02-13 TRUE MUZ1 EOF MUZ CCMT 0.0923 50 0.1084 322.0 461.00 TRUE 1.8360 0.8350 1.670 FALSE 2.330 TRUE -0.0475 TRUE 0.1040 TRUE 0.0730 FALSE -0.0322 TRUE 0.0480 1664368.000 1.3495 0.8395 535.9265 2.7795 3.8780 1181.5036 6.1277 8.5494 61.2495 0.3177 0.4432 NA NA NA NA cover
2018-02-13 TRUE PRE1 EOF PRE CCMT 0.0922 20 0.2592 8350.0 9510.00 TRUE 7.2000 -0.2900 6.910 FALSE 18.500 TRUE 0.0657 TRUE 0.0899 TRUE 0.9080 FALSE -0.0303 TRUE 0.8830 397023.252 0.3219 0.1055 3315.1442 2.7434 7.3449 7308.5668 6.0482 16.1926 199.5786 0.1652 0.4422 NA NA NA NA cover
2018-02-13 TRUE SCH1 EOF SCH CCMT 0.0969 50 0.1077 216.0 233.00 TRUE 0.8320 0.9580 1.790 FALSE 2.680 TRUE 0.0758 TRUE 0.4630 TRUE 0.0524 FALSE -0.0312 TRUE 0.0274 2064556.000 1.6740 1.9353 445.9441 3.6956 5.5330 983.1284 8.1472 12.1981 94.7137 0.7849 1.1752 NA NA NA NA cover
2018-02-13 TRUE SCH2 EOF SCH FBM 0.0907 50 0.6513 11212.0 706.00 TRUE 1.5800 1.1600 2.740 FALSE 5.280 TRUE -0.1050 TRUE 0.7020 TRUE 0.2380 FALSE -0.0268 TRUE 0.2130 935819.200 0.7588 0.9984 10492.4049 2.5641 4.9411 23131.5558 5.6529 10.8932 2536.3548 0.6198 1.1944 NA NA NA NA cover
2018-02-15 FALSE MUZ1 EOF MUZ CCMT 0.0913 50 0.1049 272.0 351.57 FALSE 0.5050 0.5670 1.070 FALSE 0.194 FALSE 0.1270 TRUE 0.2020 TRUE 0.0201 TRUE -0.0435 TRUE -0.0049 45914.370 0.0372 0.0232 12.4887 0.0491 0.0089 27.5326 0.1083 0.0196 1.4273 0.0056 0.0010 NA NA NA NA cover
2018-02-15 FALSE PRE1 EOF PRE CCMT 0.0958 50 0.1776 1636.0 2058.10 FALSE 0.9440 1.3500 2.300 FALSE 3.610 FALSE 0.2150 TRUE 0.1700 TRUE 0.1870 TRUE -0.0327 TRUE 0.1620 1014118.880 0.8223 0.2695 1659.0985 2.3325 3.6610 3657.6485 5.1422 8.0710 99.8812 0.1404 0.2204 NA NA NA NA cover
2018-02-15 FALSE PRE2 EOF PRE FBM 0.0946 50 0.1539 1186.0 1162.30 FALSE 1.1900 1.2500 2.440 FALSE 4.930 FALSE 0.0250 TRUE 0.3250 TRUE 0.3340 TRUE -0.0394 TRUE 0.3090 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-02-15 FALSE SCH1 EOF SCH CCMT 0.1016 50 0.1033 34.0 339.12 FALSE 0.5830 1.4600 2.040 FALSE 2.130 FALSE -0.0001 TRUE 0.6510 TRUE 0.0359 TRUE -0.0477 TRUE 0.0109 1100470.000 0.8923 1.0316 37.4160 2.2450 2.3440 82.4873 4.9492 5.1676 7.9468 0.4768 0.4978 NA NA NA NA cover
2018-02-15 FALSE SIM1 EOF SIM CCMT 0.0943 50 0.1024 162.0 133.98 FALSE 0.3510 0.7440 1.090 FALSE 0.050 FALSE 0.1830 TRUE 0.2620 TRUE 0.0035 TRUE -0.0456 TRUE -0.0215 7373.799 0.0060 0.0050 1.1946 0.0080 0.0004 2.6335 0.0177 0.0008 0.1843 0.0012 0.0001 NA NA NA NA cover
2018-02-15 FALSE SIM2 EOF SIM FBM 0.0940 50 0.1650 1420.0 3661.00 FALSE 1.3600 0.9990 2.350 FALSE 3.080 FALSE 0.0007 TRUE 0.1280 TRUE 0.4120 TRUE -0.0390 TRUE 0.3870 25620.490 0.0208 0.0142 36.3811 0.0602 0.0789 80.2058 0.1327 0.1740 4.5597 0.0075 0.0099 NA NA NA NA cover
2018-02-19 FALSE MUR1 EOF MUR CCMT 0.0930 50 0.1094 328.0 645.42 TRUE 1.0400 1.2900 2.330 TRUE 1.910 TRUE 0.0711 TRUE 0.1730 TRUE 0.1340 FALSE -0.0290 TRUE 0.1090 52021.280 0.0422 0.0266 17.0630 0.1212 0.0994 37.6170 0.2672 0.2191 1.9757 0.0140 0.0115 NA NA NA NA cover
2018-02-19 FALSE MUR2 EOF MUR FBM 0.0912 50 0.1081 338.0 1025.20 TRUE 1.5900 0.6720 2.260 TRUE 2.950 TRUE -0.0470 TRUE 0.1210 TRUE 0.4340 FALSE -0.0468 TRUE 0.4090 170555.900 0.1383 0.1017 57.6479 0.3855 0.5031 127.0905 0.8498 1.1092 7.8791 0.0527 0.0688 NA NA NA NA cover
2018-02-19 FALSE MUZ1 EOF MUZ CCMT 0.0935 50 0.1154 438.0 333.81 TRUE 0.8210 1.3700 2.190 TRUE 3.300 TRUE 0.0811 TRUE 0.3410 TRUE 0.0477 FALSE -0.0501 TRUE 0.0227 133518.800 0.1083 0.0673 58.4812 0.2924 0.4406 128.9277 0.6446 0.9714 6.6837 0.0334 0.0504 NA NA NA NA cover
2018-02-19 FALSE PRE1 EOF PRE CCMT 0.0933 50 0.1280 694.0 1452.40 TRUE 1.1100 1.4600 2.570 TRUE 3.300 TRUE 0.0630 TRUE 0.0986 TRUE 0.1300 FALSE -0.0463 TRUE 0.1050 874135.206 0.7088 0.2323 606.6498 2.2465 2.8846 1337.4202 4.9527 6.3595 36.5216 0.1352 0.1737 NA NA NA NA cover
2018-02-19 FALSE SCH1 EOF SCH CCMT 0.0936 50 0.1010 148.0 229.05 TRUE 0.7960 1.3900 2.150 TRUE 2.310 TRUE 0.0405 TRUE 0.1160 TRUE 0.0106 FALSE -0.0437 TRUE -0.0144 47746.010 0.0387 0.0448 7.0664 0.1027 0.1103 15.5786 0.2263 0.2432 1.5008 0.0218 0.0234 NA NA NA NA cover
2018-02-19 FALSE SIM1 EOF SIM CCMT 0.0951 50 0.1047 192.0 464.37 TRUE 0.5760 0.7640 1.340 TRUE 0.154 TRUE 0.0418 TRUE 0.0425 TRUE 0.0215 FALSE -0.0383 TRUE -0.0035 45139.310 0.0366 0.0307 8.6667 0.0605 0.0070 19.1067 0.1333 0.0153 1.3371 0.0093 0.0011 NA NA NA NA cover
2018-02-19 FALSE SIM2 EOF SIM FBM 0.0930 50 0.1395 930.0 914.13 TRUE 1.5600 0.2480 1.810 TRUE 1.020 TRUE -0.0176 TRUE -0.0066 TRUE 0.2610 FALSE -0.0356 TRUE 0.2360 109599.000 0.0889 0.0606 101.9271 0.1984 0.1118 224.7084 0.4373 0.2465 12.7748 0.0249 0.0140 NA NA NA NA cover
2018-02-23 TRUE MUR1 EOF MUR CCMT 0.0933 50 0.1409 952.0 437.00 TRUE 1.0200 2.3500 3.370 TRUE 4.260 TRUE 0.0338 TRUE 0.1580 TRUE 0.0855 FALSE -0.0425 TRUE 0.0605 2758754.000 2.2369 1.4098 2626.3338 9.2970 11.7523 5790.0155 20.4962 25.9091 304.0975 1.0765 1.3608 NA NA NA NA cover
2018-02-23 TRUE MUR2 EOF MUR FBM 0.0953 50 0.1731 1556.0 531.00 TRUE 1.1200 2.4200 3.540 TRUE 7.810 TRUE 0.0328 TRUE 0.1860 TRUE 0.2480 FALSE -0.0397 TRUE 0.2230 2445556.300 1.9830 1.4590 3805.2856 8.6573 19.0998 8389.1326 19.0858 42.1074 520.0950 1.1832 2.6105 NA NA NA NA cover
2018-02-23 TRUE MUZ1 EOF MUZ CCMT 0.0938 50 0.1074 272.0 82.60 TRUE 0.3600 0.6620 1.020 TRUE 1.570 TRUE 0.2080 TRUE 0.2200 TRUE 0.0313 FALSE -0.0396 TRUE 0.0063 1461881.000 1.1854 0.7374 397.6316 1.4911 2.2952 876.6187 3.2873 5.0599 45.4442 0.1704 0.2623 NA NA NA NA cover
2018-02-23 TRUE PRE1 EOF PRE CCMT 0.0920 20 0.2090 5850.0 3690.00 TRUE 3.6100 4.1200 7.720 TRUE 22.700 TRUE 0.0946 TRUE 0.2590 TRUE 0.4270 FALSE -0.0395 TRUE 0.4020 261916.545 0.2124 0.0696 1532.2118 2.0220 5.9455 3377.9141 4.4577 13.1075 92.2423 0.1217 0.3579 NA NA NA NA cover
2018-02-23 TRUE SIM1 EOF SIM CCMT 0.0925 50 0.1495 1140.0 314.00 TRUE 0.7680 1.1400 1.900 TRUE 3.300 TRUE 0.0343 TRUE 0.0659 TRUE 0.0606 FALSE -0.0343 TRUE 0.0356 5315815.000 4.3103 3.6195 6060.0291 10.1000 17.5422 13359.9402 22.2666 38.6735 934.9153 1.5582 2.7063 NA NA NA NA cover
2018-02-23 TRUE SIM2 EOF SIM FBM 0.0940 50 0.1626 1372.0 491.00 TRUE 0.9270 1.4900 2.410 TRUE 4.080 TRUE -0.0054 TRUE 0.0657 TRUE 0.2390 FALSE -0.0405 TRUE 0.2140 2764966.000 2.2419 1.5295 3793.5334 6.6636 11.2811 8363.2236 14.6905 24.8702 475.4533 0.8352 1.4139 NA NA NA NA cover
2018-02-26 TRUE MUR1 EOF MUR CCMT 0.0921 50 0.1163 484.0 721.00 TRUE 0.9960 0.9010 1.900 TRUE 3.130 TRUE 0.3140 TRUE 0.8580 TRUE 0.0179 FALSE -0.0385 TRUE -0.0071 1136247.000 0.9213 0.5807 549.9435 2.1589 3.5565 1212.4055 4.7594 7.8406 63.6768 0.2500 0.4118 NA NA NA NA cover
2018-02-26 TRUE MUR2 EOF MUR FBM 0.0924 20 0.1315 1955.0 261.00 TRUE 3.6700 1.2800 4.960 TRUE 7.830 TRUE 0.0732 TRUE 0.3010 TRUE 0.4220 FALSE -0.0464 TRUE 0.3970 2701281.300 2.1903 1.6115 5281.0049 13.3984 21.1510 11642.5035 29.5380 46.6296 721.7919 1.8312 2.8909 NA NA NA NA cover
2018-02-26 TRUE MUZ1 EOF MUZ CCMT 0.0918 50 0.1057 278.0 336.00 TRUE 0.5780 0.9310 1.510 TRUE 2.210 TRUE 0.0134 TRUE 0.2530 TRUE 0.0081 FALSE -0.0495 TRUE -0.0169 2113107.000 1.7134 1.0659 587.4437 3.1908 4.6700 1295.0785 7.0344 10.2954 67.1373 0.3647 0.5337 NA NA NA NA cover
2018-02-26 TRUE PRE1 EOF PRE CCMT 0.0934 20 0.2575 8205.0 9900.00 TRUE 5.6000 4.5000 10.500 TRUE 21.100 TRUE 0.0287 TRUE 0.1960 TRUE 0.1370 FALSE -0.0386 TRUE 0.1120 1943598.840 1.5759 0.5164 15947.2285 20.4078 41.0099 35157.2599 44.9910 90.4105 960.0563 1.2286 2.4689 NA NA NA NA cover
2018-02-26 TRUE SCH1 EOF SCH CCMT 0.0936 50 0.1191 510.0 639.00 TRUE 0.9830 0.9200 1.900 TRUE 3.550 TRUE 0.0133 TRUE 0.5070 TRUE 0.0318 FALSE -0.0322 TRUE 0.0068 699338.700 0.5671 0.6556 356.6627 1.3287 2.4827 786.2987 2.9293 5.4733 75.7513 0.2822 0.5273 NA NA NA NA cover
2018-02-26 TRUE SCH2 EOF SCH FBM 0.0936 20 0.1083 735.0 822.00 TRUE 1.2900 2.2500 3.530 TRUE 4.670 TRUE 0.0207 TRUE 1.2800 TRUE 0.0035 FALSE -0.0384 TRUE -0.0215 232237.000 0.1883 0.2478 170.6942 0.8198 1.0845 376.3124 1.8073 2.3910 41.2623 0.1982 0.2622 NA NA NA NA cover
2018-02-26 TRUE SIM1 EOF SIM CCMT 0.0921 20 0.1047 630.0 1020.00 TRUE 1.1100 0.4140 1.530 TRUE 2.190 TRUE 0.0659 TRUE 0.0434 TRUE 0.0667 FALSE -0.0471 TRUE 0.0417 1605864.000 1.3021 1.0934 1011.6943 2.4570 3.5168 2230.3813 5.4166 7.7532 156.0799 0.3791 0.5426 NA NA NA NA cover
2018-02-26 TRUE SIM2 EOF SIM FBM 0.0937 20 0.1305 1840.0 2450.00 TRUE 2.7900 3.1900 5.980 TRUE 4.730 TRUE 0.0142 TRUE 0.1320 TRUE 0.3360 FALSE -0.0321 TRUE 0.3110 767818.700 0.6226 0.4247 1412.7864 4.5916 3.6318 3114.6289 10.1225 8.0066 177.0682 0.5755 0.4552 NA NA NA NA cover
2018-03-02 TRUE MUR1 EOF MUR CCMT 0.0898 20 0.1993 5475.0 8940.00 TRUE 8.4500 3.3400 11.800 TRUE 19.000 TRUE 0.0814 TRUE 0.2460 TRUE 0.1940 FALSE -0.0299 TRUE 0.1690 5068846.000 4.1100 2.5904 27751.9319 59.8124 96.3081 61181.9090 131.8624 212.3208 3213.3356 6.9255 11.1513 NA NA NA NA cover
2018-03-02 TRUE MUR2 EOF MUR FBM 0.0916 20 0.1593 3385.0 4990.00 TRUE 5.0400 2.6900 7.730 TRUE 11.400 TRUE 0.0504 TRUE 0.2670 TRUE 0.1370 FALSE -0.0520 TRUE 0.1120 4615494.000 3.7424 2.7535 15623.4472 35.6778 52.6166 34443.4517 78.6552 115.9986 2135.3659 4.8763 7.1915 NA NA NA NA cover
2018-03-02 TRUE MUZ1 EOF MUZ CCMT 0.0921 50 0.1024 206.0 173.00 TRUE 0.4630 0.3180 0.781 TRUE 1.570 TRUE 0.1220 TRUE 0.2900 TRUE 0.0170 FALSE -0.0357 TRUE -0.0080 1562793.000 1.2672 0.7883 321.9354 1.2205 2.4536 709.7387 2.6908 5.4092 36.7931 0.1395 0.2804 NA NA NA NA cover
2018-03-02 TRUE MUZ2 EOF MUZ FBM 0.0913 50 0.1130 434.0 798.00 TRUE 0.8650 0.8280 1.690 TRUE 2.880 TRUE 0.0383 TRUE 0.1750 TRUE 0.0376 FALSE -0.0465 TRUE 0.0126 1274457.000 1.0334 0.6955 553.1143 2.1538 3.6704 1219.3959 4.7483 8.0918 68.3901 0.2663 0.4538 NA NA NA NA cover
2018-03-02 TRUE PRE1 EOF PRE CCMT 0.0936 50 0.1069 266.0 299.00 TRUE 0.5970 0.4940 1.090 TRUE 1.600 TRUE 0.0538 TRUE 0.1980 TRUE 0.0232 FALSE -0.0488 TRUE -0.0018 705641.523 0.5722 0.1875 187.7006 0.7691 1.1290 413.8048 1.6957 2.4891 11.3000 0.0463 0.0680 NA NA NA NA cover
2018-03-02 TRUE PRE2 EOF PRE FBM 0.0916 50 0.1381 930.0 1430.00 TRUE 1.7600 1.2800 3.040 TRUE 4.280 TRUE 0.0215 TRUE 0.2550 TRUE 0.0854 FALSE -0.0453 TRUE 0.0604 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-02 TRUE SCH1 EOF SCH CCMT 0.0924 50 0.1096 344.0 441.00 TRUE 0.8330 1.0100 1.840 TRUE 3.030 TRUE 0.0533 TRUE 0.4840 TRUE 0.0182 FALSE -0.0419 TRUE -0.0068 2527468.000 2.0494 2.3692 869.4490 4.6505 7.6582 1916.7872 10.2526 16.8833 184.6616 0.9877 1.6265 NA NA NA NA cover
2018-03-02 TRUE SCH2 EOF SCH FBM 0.0916 50 0.1578 1324.0 1320.00 TRUE 1.9100 2.1200 4.020 TRUE 5.440 TRUE 0.2000 TRUE 0.9260 TRUE 0.0111 FALSE -0.0391 TRUE -0.0139 1594111.000 1.2926 1.7008 2110.6030 6.4083 8.6720 4653.0353 14.1278 19.1182 510.2012 1.5491 2.0963 NA NA NA NA cover
2018-03-02 TRUE SIM1 EOF SIM CCMT 0.0913 50 0.0962 98.0 130.00 TRUE 0.4200 0.1920 0.612 TRUE 0.529 TRUE 0.1090 TRUE 0.0430 TRUE 0.0110 FALSE -0.0459 TRUE -0.0140 1174994.000 0.9527 0.8001 115.1494 0.7191 0.6216 253.8584 1.5853 1.3703 17.7648 0.1109 0.0959 NA NA NA NA cover
2018-03-02 TRUE SIM2 EOF SIM FBM 0.0913 50 0.1606 1386.0 7540.00 TRUE 6.4000 2.9300 9.330 TRUE 10.200 TRUE 0.0945 TRUE 0.2010 TRUE 0.2380 FALSE -0.0352 TRUE 0.2130 210527.800 0.1707 0.1165 291.7915 1.9642 2.1474 643.2836 4.3303 4.7341 36.5710 0.2462 0.2691 NA NA NA NA cover
2018-03-06 TRUE MUZ1 EOF MUZ CCMT 0.0940 20 0.1237 1485.0 1470.00 TRUE 1.9700 3.5700 5.540 FALSE 6.320 TRUE 0.0149 FALSE 0.1000 TRUE 0.0521 TRUE -0.0383 FALSE 0.0271 50584.000 0.0410 0.0255 75.1172 0.2802 0.3197 165.6035 0.6178 0.7048 8.5849 0.0320 0.0365 NA NA NA NA cover
2018-03-06 TRUE MUZ2 EOF MUZ FBM 0.0929 20 0.1307 1890.0 3000.00 TRUE 3.0400 3.8400 6.880 FALSE 8.260 TRUE 0.0147 FALSE 0.0483 TRUE 0.0274 TRUE -0.0419 FALSE 0.0024 488459.000 0.3961 0.2666 923.1875 3.3606 4.0347 2035.2592 7.4088 8.8948 114.1480 0.4155 0.4989 NA NA NA NA cover
2018-03-06 TRUE PRE1 EOF PRE CCMT 0.0900 20 0.1632 3660.0 6300.00 TRUE 5.4700 4.0700 9.540 FALSE 11.600 TRUE 0.0027 FALSE 0.0465 TRUE 0.0817 TRUE -0.0478 FALSE 0.0567 27692.490 0.0225 0.0074 101.3545 0.2642 0.3212 223.4462 0.5824 0.7082 6.1018 0.0159 0.0193 NA NA NA NA cover
2018-03-06 TRUE PRE2 EOF PRE FBM 0.0915 20 0.1771 4280.0 8210.00 TRUE 6.0600 5.8800 11.900 FALSE 14.500 TRUE 0.0898 FALSE 0.0711 TRUE 0.1010 TRUE -0.0510 FALSE 0.0760 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-06 TRUE SIM2 EOF SIM FBM 0.0916 20 0.1376 2300.0 3880.00 TRUE 3.8000 1.8500 5.650 FALSE 5.740 TRUE 0.0519 FALSE 0.0094 TRUE 0.0936 TRUE -0.0414 FALSE 0.0686 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-12 TRUE MUR2 EOF MUR FBM 0.0925 20 0.1345 2100.0 1500.00 TRUE 2.8300 3.0000 5.830 TRUE 6.430 TRUE 0.0918 FALSE 0.1040 TRUE 0.3590 TRUE -0.0315 FALSE 0.3340 814373.570 0.6603 0.4858 1710.1845 4.7478 5.2364 3770.2727 10.4670 11.5442 233.7429 0.6489 0.7157 NA NA NA NA cover
2018-03-12 TRUE MUZ1 EOF MUZ CCMT 0.0912 20 0.1948 5180.0 3160.00 TRUE 3.1900 13.1000 16.300 TRUE 18.100 TRUE 0.0747 FALSE 0.0894 TRUE 0.0878 TRUE -0.0448 FALSE 0.0628 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-12 TRUE MUZ2 EOF MUZ FBM 0.0949 50 0.1124 350.0 115.00 TRUE 0.3890 1.4400 1.830 TRUE 1.890 TRUE 0.1100 FALSE 0.0433 TRUE 0.0654 TRUE -0.0475 FALSE 0.0404 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-12 TRUE SIM1 EOF SIM CCMT 0.0925 20 0.1782 4285.0 2100.00 TRUE 1.8100 2.8200 4.630 TRUE 4.630 TRUE 0.0348 FALSE 0.0228 TRUE 0.1490 TRUE -0.0522 FALSE 0.1240 577852.400 0.4685 0.3935 2476.0975 2.6755 2.6755 5458.8046 5.8983 5.8983 382.0017 0.4128 0.4128 NA NA NA NA cover
2018-03-29 TRUE MUR1 EOF MUR CCMT 0.0938 50 0.0966 56.0 64.20 TRUE 1.8900 56.4000 58.300 TRUE 1.060 TRUE 2.8600 FALSE -0.0108 TRUE 0.0687 FALSE -0.0576 FALSE 0.0437 3082688.000 2.4996 1.5754 172.6305 179.7207 3.2676 380.5813 396.2123 7.2039 19.9885 20.8095 0.3784 NA NA NA NA cover
2018-03-29 TRUE MUR2 EOF MUR FBM 0.0928 20 0.2694 8830.0 6000.00 TRUE 7.9500 20.6000 28.600 TRUE 19.000 TRUE 1.2900 FALSE 0.0040 TRUE 1.9000 FALSE -0.0495 FALSE 1.8750 1407768.000 1.1415 0.8398 12430.5914 40.2622 26.7476 27404.4819 88.7620 58.9677 1698.9759 5.5029 3.6558 NA NA NA NA cover
2018-03-29 TRUE PRE1 EOF PRE CCMT 0.0933 20 0.1590 3285.0 7250.00 TRUE 7.2100 3.1500 10.400 TRUE 16.100 TRUE 0.2830 FALSE 0.0464 TRUE 0.7890 FALSE -0.0629 FALSE 0.7640 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-29 TRUE PRE2 EOF PRE FBM 0.0936 20 0.1426 2450.0 4580.00 TRUE 5.8400 1.0400 6.880 TRUE 11.400 TRUE 0.3830 FALSE 0.0610 TRUE 1.0300 FALSE -0.0623 FALSE 1.0050 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-29 TRUE SCH1 EOF SCH CCMT 0.0920 50 0.0960 80.0 72.70 TRUE 0.5940 0.6800 1.270 TRUE 1.530 TRUE 0.2140 FALSE 0.0823 TRUE 0.1100 FALSE -0.0583 FALSE 0.0850 457618.000 0.3711 0.4290 36.6094 0.5812 0.7002 80.7092 1.2813 1.5436 7.7755 0.1234 0.1487 NA NA NA NA cover
2018-03-29 TRUE SCH2 EOF SCH FBM 0.0937 50 0.0993 112.0 143.00 TRUE 0.8850 0.6780 1.560 TRUE 3.040 TRUE 0.0750 FALSE 0.2370 TRUE 0.2300 FALSE -0.0593 FALSE 0.2050 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-03-29 TRUE SIM1 EOF SIM CCMT 0.0928 20 0.1353 2125.0 3600.00 TRUE 3.8000 -0.0850 3.720 TRUE 5.030 TRUE 0.2950 FALSE 0.0090 TRUE 0.0081 FALSE -0.0631 FALSE -0.0169 68542.630 0.0556 0.0467 145.6531 0.2550 0.3448 321.1068 0.5621 0.7601 22.4707 0.0393 0.0532 NA NA NA NA cover
2018-03-29 TRUE SIM2 EOF SIM FBM 0.0933 50 0.1143 420.0 785.00 TRUE 3.4800 -0.2210 3.260 TRUE 1.460 TRUE 0.0641 FALSE -0.0060 TRUE 1.9900 FALSE -0.0600 FALSE 1.9650 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-04-17 TRUE MUR2 EOF MUR FBM 0.0937 20 0.1090 765.0 2231.30 TRUE 5.3600 0.9080 6.270 TRUE 2.060 TRUE 0.7960 FALSE 0.0620 TRUE 2.2800 FALSE 0.0358 FALSE 2.2550 4773919.000 3.8709 2.8480 3652.0480 29.9325 9.8343 8051.3051 65.9891 21.6806 499.1510 4.0911 1.3441 NA NA NA NA cover
2018-04-17 TRUE MUZ2 EOF MUZ FBM 0.0934 20 0.0995 305.0 946.54 TRUE 1.0100 1.3700 2.380 TRUE 0.239 TRUE 0.1940 FALSE 0.0802 TRUE 0.0431 FALSE -0.0601 FALSE 0.0181 1016568.000 0.8243 0.5548 310.0532 2.4194 0.2430 683.5434 5.3339 0.5356 38.3367 0.2992 0.0300 NA NA NA NA cover
2018-04-17 TRUE SCH1 EOF SCH CCMT 0.0884 50 0.0955 142.0 146.21 TRUE 0.6070 0.9980 1.600 TRUE 1.080 TRUE 0.2470 FALSE 0.0671 TRUE 0.1090 FALSE -0.0588 FALSE 0.0840 1346638.000 1.0919 1.2623 191.2226 2.1546 1.4544 421.5693 4.7501 3.2063 40.6136 0.4576 0.3089 NA NA NA NA cover
2018-04-17 TRUE SIM1 EOF SIM CCMT 0.0934 50 0.0985 102.0 496.60 TRUE 4.1600 3.4500 7.620 TRUE 2.700 TRUE 2.5100 FALSE 0.1800 TRUE 3.1400 FALSE 0.0209 FALSE 3.1150 552394.000 0.4479 0.3761 56.3442 4.2092 1.4915 124.2164 9.2797 3.2881 8.6925 0.6494 0.2301 NA NA NA NA cover
2018-04-24 TRUE CAR1 EOF CAR CCMT 0.0920 20 0.1311 1955.0 570.00 FALSE 10.4000 6.5800 17.000 TRUE 4.350 TRUE 0.8190 FALSE -0.0167 TRUE 7.1800 FALSE 0.0083 FALSE 7.1550 8718.000 0.0071 0.0038 17.0437 0.1482 0.0379 37.5745 0.3267 0.0836 1.6804 0.0146 0.0037 NA NA NA NA cover
2018-04-24 TRUE CAR2 EOF CAR FBM 0.0919 20 0.1677 3790.0 1846.00 FALSE 10.9000 5.2400 16.100 TRUE 7.340 TRUE 1.0700 FALSE 0.0566 TRUE 4.8000 FALSE -0.0558 FALSE 4.7750 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2018-04-24 TRUE MUR2 EOF MUR FBM 0.0927 20 0.1257 1650.0 1470.00 FALSE 4.3600 0.0270 4.380 TRUE 3.710 TRUE 0.3840 FALSE 0.1060 TRUE 0.7340 FALSE -0.0340 FALSE 0.7090 52693.210 0.0427 0.0314 86.9438 0.2308 0.1955 191.6763 0.5088 0.4310 11.8832 0.0315 0.0267 NA NA NA NA cover
2018-04-24 TRUE MUZ2 EOF MUZ FBM 0.0926 50 0.1255 658.0 810.00 FALSE 1.6800 1.7600 3.430 TRUE 0.525 TRUE 0.2190 FALSE 0.0657 TRUE 0.5130 FALSE -0.0500 FALSE 0.4880 19762.000 0.0160 0.0108 13.0034 0.0678 0.0104 28.6673 0.1494 0.0229 1.6078 0.0084 0.0013 NA NA NA NA cover
2018-04-24 TRUE SCH1 EOF SCH CCMT 0.0899 50 0.0945 92.0 201.00 FALSE 0.8830 1.4300 2.320 TRUE 0.129 TRUE 0.3970 FALSE 0.0990 TRUE 0.1130 FALSE -0.0529 FALSE 0.0880 24596.000 0.0199 0.0231 2.2628 0.0571 0.0032 4.9886 0.1258 0.0070 0.4806 0.0121 0.0007 NA NA NA NA cover
2018-04-24 TRUE SIM1 EOF SIM CCMT 0.0912 50 0.1124 424.0 869.00 FALSE 11.0000 2.2600 13.300 TRUE 2.260 TRUE 1.9500 FALSE 0.0522 TRUE 7.8600 FALSE 0.1040 FALSE 7.7560 77616.000 0.0629 0.0528 32.9092 1.0323 0.1754 72.5516 2.2758 0.3867 5.0771 0.1593 0.0271 NA NA NA NA cover
2018-05-18 TRUE CAR1 EOF CAR CCMT 0.0941 20 0.1649 3540.0 2560.00 TRUE 24.1000 8.7000 32.800 TRUE 10.000 TRUE 4.0900 TRUE 0.0691 FALSE 10.3000 TRUE 0.2040 TRUE 10.0960 184232.000 0.1494 0.0802 652.1813 6.0428 1.8423 1437.7988 13.3220 4.0616 64.3023 0.5958 0.1816 NA NA NA NA cash
2018-05-18 TRUE PRE1 EOF PRE CCMT 0.0928 20 0.2381 7265.0 8900.00 TRUE 7.8400 4.1500 12.000 TRUE 18.500 TRUE 0.7170 TRUE 0.0506 FALSE 2.2200 TRUE -0.5100 TRUE 2.1950 2714047.000 2.2007 0.7211 19717.5515 32.5686 50.2099 43469.3139 71.8007 110.6927 1187.0375 1.9607 3.0227 NA NA NA NA cash
2018-05-18 TRUE PRE2 EOF PRE FBM 0.0928 20 0.2434 7530.0 10340.00 TRUE 8.8800 3.1000 12.000 TRUE 20.600 TRUE 0.2400 TRUE 0.0769 FALSE 1.2300 TRUE -0.5130 TRUE 1.2050 3323537.000 2.6949 0.8654 25026.2336 39.8824 68.4649 55172.8346 87.9248 150.9376 1476.3938 2.3528 4.0390 NA NA NA NA cash
2018-05-23 TRUE MUR2 EOF MUR FBM 0.0913 20 0.1652 3695.0 5650.00 FALSE 9.8000 9.5300 19.300 FALSE 13.800 TRUE 2.7200 TRUE 0.0688 FALSE 5.7600 TRUE -0.4330 TRUE 5.7350 4679.781 0.0038 0.0028 17.2918 0.0903 0.0646 38.1215 0.1991 0.1424 2.3634 0.0123 0.0088 NA NA NA NA cash
2018-05-23 TRUE MUZ1 EOF MUZ CCMT 0.0960 20 0.1427 2335.0 2050.00 FALSE 3.2300 3.2400 6.460 FALSE 2.720 TRUE 0.2790 TRUE 0.0924 FALSE 1.5000 TRUE -0.5020 TRUE 1.4750 513706.000 0.4165 0.2591 1199.5035 3.3185 1.3973 2644.4254 7.3161 3.0804 137.0879 0.3793 0.1597 NA NA NA NA cash
2018-05-23 TRUE MUZ2 EOF MUZ FBM 0.0959 20 0.1426 2335.0 2780.00 FALSE 3.1500 3.3800 6.530 FALSE 7.680 TRUE 0.1340 TRUE 0.0764 FALSE 1.3200 TRUE 0.0250 TRUE 1.2950 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-05-23 TRUE PRE1 EOF PRE CCMT 0.0934 20 0.2177 6215.0 708.00 FALSE 7.4700 1.4400 8.910 FALSE 11.600 TRUE 0.3350 TRUE 0.0854 FALSE 2.1600 TRUE -0.5080 TRUE 2.1350 1959087.000 1.5885 0.5205 12175.7257 17.4555 22.7254 26842.6049 38.4823 50.1004 733.0040 1.0509 1.3681 NA NA NA NA cash
2018-05-23 TRUE PRE2 EOF PRE FBM 0.0921 20 0.1448 2635.0 6320.00 FALSE 6.8400 1.6800 8.520 FALSE 9.800 TRUE 0.2330 TRUE 0.0870 FALSE 2.1000 TRUE -0.5000 TRUE 2.0750 3433679.000 2.7842 0.8940 9047.7442 29.2549 33.6501 19946.6568 64.4955 74.1849 533.7612 1.7259 1.9851 NA NA NA NA cash
2018-05-23 TRUE SCH1 EOF SCH CCMT 0.0918 50 0.1164 492.0 700.00 FALSE 1.9000 2.1900 4.080 FALSE 5.070 TRUE 0.6010 TRUE 0.4630 FALSE 0.2480 TRUE -0.5150 TRUE 0.2230 477598.100 0.3873 0.4477 234.9783 1.9486 2.4214 518.0331 4.2959 5.3383 49.9068 0.4139 0.5143 NA NA NA NA cash
2018-05-23 TRUE SCH2 EOF SCH FBM 0.0942 50 0.1175 466.0 563.00 FALSE 4.2900 1.1100 5.400 FALSE 4.380 TRUE 2.7100 TRUE 0.3030 FALSE 4.5700 TRUE -0.5140 TRUE 4.5450 433455.000 0.3515 0.4625 201.9900 2.3407 1.8985 445.3072 5.1602 4.1855 48.8275 0.5658 0.4589 NA NA NA NA cash
2018-05-30 TRUE CAR1 EOF CAR CCMT 0.0924 30 0.2392 4893.3 3330.00 TRUE 5.1300 2.1300 7.260 TRUE 49.500 TRUE 3.4500 TRUE 0.1240 TRUE 6.8100 FALSE -0.0377 TRUE 6.7850 401364.000 0.3254 0.1747 1964.0078 2.9139 19.8675 4329.8517 6.4240 43.7999 193.6427 0.2873 1.9589 NA NA NA NA cash
2018-05-30 TRUE MUZ1 EOF MUZ CCMT 0.0935 30 0.0961 86.7 135.00 TRUE 0.8340 -0.5410 0.292 TRUE 1.440 TRUE 0.1400 TRUE 0.1250 TRUE 0.1630 FALSE -0.0761 TRUE 0.1380 390191.000 0.3164 0.1968 33.8166 0.1139 0.5619 74.5520 0.2512 1.2387 3.8648 0.0130 0.0642 NA NA NA NA cash
2018-05-30 TRUE MUZ2 EOF MUZ FBM 0.0906 30 0.0937 103.3 188.00 TRUE 0.7770 -0.5970 0.181 TRUE 1.950 TRUE 0.2460 TRUE 0.1310 TRUE 0.3820 FALSE -0.0718 TRUE 0.3570 702216.000 0.5694 0.3832 72.5623 0.1271 1.3693 159.9709 0.2802 3.0188 8.9720 0.0157 0.1693 NA NA NA NA cash
2018-05-30 TRUE PRE1 EOF PRE CCMT 0.0903 30 0.2538 5450.0 6450.00 TRUE 6.3500 5.6900 12.000 TRUE 18.900 TRUE 0.1080 TRUE 0.0594 TRUE 0.3500 FALSE -0.0689 TRUE 0.3250 3484434.000 2.8253 0.9258 18990.1653 41.8132 65.8558 41865.7184 92.1814 145.1857 1143.2474 2.5172 3.9647 NA NA NA NA cash
2018-05-30 TRUE PRE2 EOF PRE FBM 0.0941 30 0.2278 4456.7 7880.00 TRUE 6.5000 6.1400 12.600 TRUE 16.400 TRUE 0.1700 TRUE 0.1140 TRUE 1.2700 FALSE -0.0637 TRUE 1.2450 3945699.000 3.1993 1.0273 17584.6652 49.7158 64.7095 38767.1529 109.6035 142.6585 1037.3870 2.9329 3.8175 NA NA NA NA cash
2018-06-05 TRUE MUZ2 EOF MUZ FBM 0.0945 30 0.1078 443.3 472.00 TRUE 0.7230 0.8340 1.560 FALSE 2.530 TRUE 0.1260 TRUE 0.1100 TRUE 0.0035 FALSE -0.0743 TRUE -0.0215 171305.000 0.1389 0.0935 75.9452 0.2672 0.4334 167.4288 0.5891 0.9555 9.3903 0.0330 0.0536 NA NA NA NA cash
2018-06-14 FALSE MUR2 EOF MUR FBM 0.0894 30 0.1357 1543.3 620.00 TRUE 25.2000 27.7000 52.900 TRUE 44.500 FALSE 0.6080 TRUE 0.0799 TRUE 6.0200 FALSE 0.1200 TRUE 5.9000 3207197.000 2.6005 1.9133 4949.7740 169.6607 142.7203 10912.2718 374.0340 314.6411 676.5203 23.1887 19.5066 NA NA NA NA cash
2018-06-14 FALSE PRE1 EOF PRE CCMT 0.0976 30 0.1916 3133.3 3000.00 TRUE 4.7700 3.8500 8.620 TRUE 2.590 FALSE 0.3610 TRUE 0.5100 TRUE 1.6000 FALSE -0.0520 TRUE 1.5750 7110.000 0.0058 0.0019 22.2780 0.0613 0.0184 49.1141 0.1351 0.0406 1.3412 0.0037 0.0011 NA NA NA NA cash
2018-06-14 FALSE SIM1 EOF SIM CCMT 0.0915 30 1.0131 30720.0 22000.00 TRUE 7.8100 7.4400 15.300 TRUE 6.910 FALSE 3.0600 TRUE 0.0624 TRUE 2.1200 FALSE 0.0116 TRUE 2.0950 141283.000 0.1146 0.0962 4340.2138 2.1616 0.9763 9568.4353 4.7655 2.1523 669.5896 0.3335 0.1506 NA NA NA NA cash
2018-06-25 TRUE CAR1 EOF CAR CCMT 0.2479 50 0.2684 410.0 497.00 FALSE 4.2900 1.6300 5.910 TRUE 3.570 TRUE 0.8990 TRUE 0.2780 TRUE 0.5650 FALSE 0.6400 TRUE -0.0750 1113947.000 0.9032 0.4847 456.7183 6.5834 3.9768 1006.8811 14.5138 8.7672 45.0305 0.6491 0.3921 NA NA NA NA cash
2018-06-25 TRUE MUR2 EOF MUR FBM 0.2486 20 0.3022 2680.0 2180.00 FALSE 7.6900 3.2900 11.000 TRUE 8.970 TRUE 0.2780 TRUE 0.1400 TRUE 1.0300 FALSE 0.4660 TRUE 0.5640 7188283.000 5.8286 4.2883 19264.5984 79.0711 64.4789 42470.7337 174.3202 142.1502 2633.0275 10.8072 8.8128 NA NA NA NA cash
2018-06-25 TRUE MUZ1 EOF MUZ CCMT 0.2517 20 0.3208 3455.0 2320.00 FALSE 5.1200 2.2400 7.360 TRUE 10.700 TRUE 0.1740 TRUE 0.1340 TRUE 0.0268 FALSE 0.0202 TRUE 0.0018 1239224.000 1.0048 0.6251 4281.5189 9.1207 13.2597 9439.0366 20.1075 29.2323 489.3228 1.0424 1.5154 NA NA NA NA cash
2018-06-25 TRUE MUZ2 EOF MUZ FBM 0.2486 50 0.2812 652.0 586.00 FALSE 1.6000 0.3250 1.920 TRUE 2.940 TRUE 0.0306 TRUE 0.0919 TRUE 0.0035 FALSE 0.0236 TRUE -0.0215 388013.000 0.3146 0.2117 252.9845 0.7450 1.1408 557.7296 1.6424 2.5149 31.2804 0.0921 0.1410 NA NA NA NA cash
2018-06-25 TRUE PRE2 EOF PRE FBM 0.2462 20 0.3562 5500.0 5660.00 FALSE 7.6900 0.3550 8.040 TRUE 12.800 TRUE 0.0554 TRUE 0.2540 TRUE 0.0035 FALSE 0.0137 TRUE -0.0215 1996400.000 1.6188 0.5198 10980.2000 16.0511 25.5539 24206.9489 35.3862 56.3362 647.7642 0.9469 1.5075 NA NA NA NA cash
2018-06-25 TRUE SCH1 EOF SCH CCMT 0.2472 50 0.2777 610.0 481.00 FALSE 2.2300 1.3900 3.620 TRUE 3.600 TRUE 0.0835 TRUE 0.2970 TRUE 0.0233 FALSE 0.0226 TRUE -0.0017 1027122.000 0.8328 0.9628 626.5444 3.7182 3.6976 1381.2798 8.1971 8.1518 133.0713 0.7897 0.7853 NA NA NA NA cash
2018-06-25 TRUE SIM1 EOF SIM CCMT 0.2507 50 0.2879 744.0 470.00 FALSE 21.3000 2.2800 23.500 TRUE 3.280 TRUE 2.2700 TRUE 0.1050 TRUE 2.4100 FALSE 1.7400 TRUE 0.6700 295863.000 0.2399 0.2015 220.1221 6.9528 0.9704 485.2811 15.3281 2.1394 33.9595 1.0726 0.1497 NA NA NA NA cash
2018-07-06 TRUE CAR1 EOF CAR CCMT 0.0933 40 0.2276 3357.5 2580.00 TRUE 11.2000 4.9300 16.100 FALSE 9.790 TRUE 0.1300 TRUE 0.2110 TRUE 0.0035 FALSE 0.0119 TRUE -0.0215 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-07-06 TRUE MUR2 EOF MUR FBM 0.0938 40 0.1074 340.0 168.00 TRUE 2.4600 0.4810 2.940 FALSE 1.780 TRUE 0.1220 TRUE 0.0903 TRUE 0.2060 FALSE 0.2110 TRUE -0.0050 768363.000 0.6230 0.4584 261.2434 2.2590 1.3677 575.9372 4.9802 3.0152 35.7060 0.3088 0.1869 NA NA NA NA cash
2018-07-06 TRUE MUZ1 EOF MUZ CCMT 0.0932 40 0.1012 200.0 84.90 TRUE 0.5260 0.4100 0.936 FALSE 1.430 TRUE 0.0438 TRUE 0.0912 TRUE 0.0035 FALSE 0.0248 TRUE -0.0215 541106.000 0.4388 0.2729 108.2212 0.5065 0.7738 238.5845 1.1166 1.7059 12.3683 0.0579 0.0884 NA NA NA NA cash
2018-07-06 TRUE MUZ2 EOF MUZ FBM 0.0952 40 0.1016 160.0 133.00 TRUE 0.5780 0.3920 0.970 FALSE 1.540 TRUE 0.0369 TRUE 0.0754 TRUE 0.2580 FALSE 0.3330 TRUE -0.0750 250687.000 0.2033 0.1368 40.1099 0.2432 0.3861 88.4263 0.5361 0.8511 4.9594 0.0301 0.0477 NA NA NA NA cash
2018-07-06 TRUE PRE1 EOF PRE CCMT 0.0922 40 0.2350 3570.0 4040.00 TRUE 4.3500 1.7900 6.150 FALSE 10.600 TRUE -0.0254 TRUE 0.1890 TRUE 0.0035 FALSE 0.0137 TRUE -0.0215 2167.000 0.0018 0.0006 7.7362 0.0133 0.0230 17.0552 0.0294 0.0506 0.4657 0.0008 0.0014 NA NA NA NA cash
2018-07-06 TRUE SIM1 EOF SIM CCMT 0.0926 40 0.0993 167.5 57.70 TRUE 3.3600 0.5820 3.950 FALSE 0.717 TRUE 0.2860 TRUE 0.0541 TRUE 0.3800 FALSE -0.0770 TRUE 0.3550 268874.000 0.2180 0.1831 45.0364 1.0621 0.1928 99.2872 2.3414 0.4250 6.9480 0.1638 0.0297 NA NA NA NA cash
2018-07-13 TRUE MUR1 EOF MUR CCMT 0.0934 35 0.1892 2737.1 NA FALSE 7.9000 -0.1070 7.790 TRUE 5.950 TRUE 0.0286 TRUE 0.2240 TRUE 0.2210 TRUE 0.2440 TRUE -0.0230 229513.000 0.1861 0.1173 628.2099 1.7879 1.3656 1384.9515 3.9416 3.0106 72.7390 0.2070 0.1581 NA NA NA NA cash
2018-07-13 TRUE MUR2 EOF MUR FBM 0.0924 35 0.1218 840.0 NA FALSE 2.5600 0.9360 3.490 TRUE 3.610 TRUE -0.0009 TRUE 0.1750 TRUE 0.0267 TRUE 0.0528 TRUE -0.0261 301596.000 0.2445 0.1799 253.3406 1.0526 1.0888 558.5148 2.3205 2.4003 34.6258 0.1439 0.1488 NA NA NA NA cash
2018-07-13 TRUE SCH2 EOF SCH FBM 0.0944 40 0.1126 455.0 NA FALSE 0.5470 0.6140 1.160 TRUE 1.830 TRUE 0.0421 TRUE 0.0942 TRUE 0.0035 TRUE 0.0436 TRUE -0.0215 715429.000 0.5801 0.7633 325.5202 0.8299 1.3092 717.6418 1.8296 2.8863 78.6888 0.2006 0.3165 NA NA NA NA cash
2018-07-19 FALSE CAR1 EOF CAR CCMT 0.0947 50 0.1865 1836.0 1530.00 TRUE 12.4000 4.3300 16.700 TRUE 11.100 TRUE 0.0812 TRUE 0.3810 TRUE 0.2240 FALSE -0.1460 FALSE 0.1990 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-07-19 FALSE PRE1 EOF PRE CCMT 0.0939 50 0.1146 414.0 507.00 TRUE 0.7210 1.0600 1.780 TRUE 2.730 TRUE -0.0095 TRUE 0.3580 TRUE 0.0035 FALSE -0.4370 FALSE -0.0215 1258655.000 1.0206 0.3344 521.0832 2.2404 3.4361 1148.7800 4.9392 7.5753 31.3703 0.1349 0.2069 NA NA NA NA cash
2018-07-19 FALSE PRE2 EOF PRE FBM 0.0925 50 0.1360 870.0 561.00 TRUE 1.4100 1.3400 2.750 TRUE 3.490 TRUE -0.0175 TRUE 0.3530 TRUE 0.0122 FALSE -0.3890 FALSE -0.0128 4594725.000 3.7256 1.1963 3997.4108 12.6355 16.0356 8812.6917 27.8562 35.3521 235.8226 0.7454 0.9460 NA NA NA NA cash
2018-07-19 FALSE SCH1 EOF SCH CCMT 0.0939 50 0.1011 144.0 59.50 TRUE 0.9550 0.7910 1.750 TRUE 1.640 TRUE 0.0366 TRUE 2.6200 TRUE 0.0371 FALSE -0.3050 FALSE 0.0121 1746700.000 1.4163 1.6373 251.5248 3.0567 2.8646 554.5116 6.7389 6.3153 53.4212 0.6492 0.6084 NA NA NA NA cash
2018-07-19 FALSE SIM1 EOF SIM CCMT 0.0916 25 0.2462 6184.0 5760.00 TRUE 8.0100 9.8900 17.900 TRUE 10.800 TRUE 1.4000 TRUE 0.3690 TRUE 0.0035 FALSE -0.4030 FALSE -0.0215 118117.000 0.0958 0.0804 730.4355 2.1143 1.2757 1610.3182 4.6612 2.8123 112.6885 0.3262 0.1968 NA NA NA NA cash
2018-07-23 TRUE MUR1 EOF MUR CCMT 0.0917 30 0.2958 6803.3 8320.00 TRUE 9.6300 7.3500 17.000 TRUE 14.200 TRUE 0.1670 TRUE 0.2630 TRUE 0.0035 FALSE -0.3960 FALSE -0.0215 99207.000 0.0804 0.0507 674.9383 1.6865 1.4087 1487.9690 3.7181 3.1057 78.1496 0.1953 0.1631 NA NA NA NA cash
2018-07-23 TRUE MUR2 EOF MUR FBM 0.0930 30 0.1619 2296.7 2650.00 TRUE 3.3900 2.9700 6.360 TRUE 8.460 TRUE 0.0426 TRUE 0.2070 TRUE 0.0035 FALSE -0.4400 FALSE -0.0215 181414.000 0.1471 0.1082 416.6475 1.1538 1.5348 918.5410 2.5437 3.3835 56.9461 0.1577 0.2098 NA NA NA NA cash
2018-07-23 TRUE MUZ1 EOF MUZ CCMT 0.0909 50 0.0963 108.0 46.00 TRUE 0.4430 0.7920 1.250 TRUE 1.270 TRUE 0.0833 TRUE 0.1570 TRUE 0.2870 FALSE -0.0987 FALSE 0.2620 627259.000 0.5086 0.3164 67.7440 0.7841 0.7966 149.3484 1.7286 1.7562 7.7423 0.0896 0.0910 NA NA NA NA cash
2018-07-23 TRUE MUZ2 EOF MUZ FBM 0.0938 30 0.1029 303.3 267.00 TRUE 3.4200 2.0000 5.430 TRUE 3.300 TRUE 0.5910 TRUE 0.3660 TRUE 0.2200 FALSE -0.1730 FALSE 0.1950 45359.000 0.0368 0.0248 13.7589 0.2463 0.1497 30.3329 0.5430 0.3300 1.7012 0.0305 0.0185 NA NA NA NA cash
2018-07-23 TRUE PRE1 EOF PRE CCMT 0.0935 30 0.4252 11056.7 7230.00 TRUE 7.0700 3.6900 10.800 TRUE 12.600 TRUE 0.0489 TRUE 0.1610 TRUE 0.0172 FALSE -0.3870 FALSE -0.0078 618285.000 0.5013 0.1643 6836.1712 6.6775 7.7904 15071.0229 14.7212 17.1747 411.5517 0.4020 0.4690 NA NA NA NA cash
2018-07-23 TRUE PRE2 EOF PRE FBM 0.0926 50 0.0994 136.0 134.00 TRUE 0.6830 1.6300 2.310 TRUE 1.630 TRUE 0.1970 TRUE 0.3270 TRUE 0.0035 FALSE -0.3970 FALSE -0.0215 1900935.000 1.5414 0.4949 258.5272 4.3912 3.0985 569.9490 9.6808 6.8310 15.2515 0.2591 0.1828 NA NA NA NA cash
2018-07-23 TRUE SIM1 EOF SIM CCMT 0.0926 50 0.1475 1098.0 526.00 TRUE 12.0000 2.1700 14.200 TRUE 3.730 TRUE 0.1450 TRUE 0.2320 TRUE 0.6800 FALSE 0.3840 FALSE 0.2960 106540.000 0.0864 0.0725 116.9809 1.5129 0.3974 257.8961 3.3353 0.8761 18.0473 0.2334 0.0613 NA NA NA NA cash
2018-07-31 FALSE MUR1 EOF MUR CCMT 0.0928 20 0.2117 5945.0 6430.00 TRUE 6.9300 2.4700 9.400 TRUE 12.000 TRUE 0.1590 TRUE 0.3330 TRUE 0.0956 FALSE -0.2890 FALSE 0.0706 47765.000 0.0387 0.0244 283.9629 0.4490 0.5732 626.0247 0.9898 1.2636 32.8794 0.0520 0.0664 NA NA NA NA cash
2018-07-31 FALSE MUZ2 EOF MUZ FBM 0.0927 20 0.0972 225.0 126.00 TRUE 0.6610 0.5790 1.240 TRUE 1.420 TRUE -0.0364 TRUE 0.1410 TRUE 0.0035 FALSE -0.4020 FALSE -0.0215 55551.000 0.0450 0.0303 12.4990 0.0689 0.0789 27.5552 0.1519 0.1739 1.5454 0.0085 0.0098 NA NA NA NA cash
2018-07-31 FALSE PRE1 EOF PRE CCMT 0.0944 20 0.1293 1745.0 585.00 TRUE 1.6900 0.0450 1.730 TRUE 4.110 TRUE -0.0217 TRUE 0.2580 TRUE 0.0966 FALSE -0.2660 FALSE 0.0716 2028901.000 1.6451 0.5391 3540.4322 3.5100 8.3388 7805.2369 7.7381 18.3837 213.1414 0.2113 0.5020 NA NA NA NA cash
2018-07-31 FALSE SCH1 EOF SCH CCMT 0.0938 20 0.0952 70.0 15.70 TRUE 0.3380 0.2170 0.599 TRUE 1.070 TRUE 0.0361 TRUE 0.2710 TRUE 0.0390 FALSE -0.3890 FALSE 0.0140 799175.000 0.6480 0.7491 55.9422 0.4787 0.8551 123.3303 1.0554 1.8852 11.8815 0.1017 0.1816 NA NA NA NA cash
2018-07-31 FALSE SCH2 EOF SCH FBM 0.0937 20 0.0962 125.0 59.80 TRUE 6.6800 -6.4200 0.258 TRUE 1.220 TRUE 0.0680 TRUE 0.1480 TRUE 0.1070 FALSE -0.2590 FALSE 0.0820 718728.000 0.5828 0.7668 89.8410 0.1854 0.8768 198.0635 0.4088 1.9331 21.7175 0.0448 0.2120 NA NA NA NA cash
2018-09-11 FALSE CAR1 EOF CAR CCMT 0.0933 20 0.1208 1375.0 960.00 FALSE NA NA 8.440 TRUE 7.840 TRUE 0.1550 FALSE 21.2000 TRUE 0.6900 FALSE -0.0440 TRUE 0.6650 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-09-11 FALSE MUR1 EOF MUR CCMT 0.0923 20 0.1771 4240.0 4472.00 FALSE NA NA 3.540 TRUE 3.520 TRUE -0.0082 FALSE 0.5710 TRUE 0.1500 FALSE -0.0419 TRUE 0.1250 2628348.000 2.1312 1.3432 11144.1955 9.3044 9.2518 24568.4934 20.5124 20.3965 1290.3621 1.0773 1.0712 NA NA NA NA cash
2018-09-11 FALSE MUR2 EOF MUR FBM 0.0913 20 0.1160 1235.0 2024.00 FALSE NA NA 4.850 TRUE 5.610 TRUE 0.0743 FALSE 0.6260 TRUE 0.0035 FALSE -0.0482 TRUE -0.0215 1154103.000 0.9358 0.6885 1425.3172 5.5974 6.4745 3142.2543 12.3400 14.2737 194.8081 0.7650 0.8849 NA NA NA NA cash
2018-09-11 FALSE MUZ1 EOF MUZ CCMT 0.0935 20 0.1504 2845.0 2620.00 FALSE NA NA 11.400 TRUE 9.680 TRUE 0.0719 FALSE 0.6500 TRUE 2.5500 FALSE -0.0457 TRUE 2.5250 3594904.000 2.9149 1.8133 10227.5019 40.9819 34.7987 22547.5506 90.3487 76.7171 1168.8725 4.6837 3.9770 NA NA NA NA cash
2018-09-11 FALSE MUZ2 EOF MUZ FBM 0.0931 30 0.1033 340.0 373.00 FALSE NA NA 4.900 TRUE 3.220 TRUE 0.0707 FALSE 0.9210 TRUE 2.7100 FALSE -0.0446 TRUE 2.6850 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-09-11 FALSE PRE2 EOF PRE FBM 0.0939 30 0.0969 100.0 86.90 FALSE NA NA 2.590 TRUE 0.498 TRUE 0.3630 FALSE 0.3810 TRUE 0.0262 FALSE -0.0436 TRUE 0.0012 902238.000 0.7316 0.2349 90.2238 2.3368 0.4493 198.9074 5.1517 0.9906 5.3226 0.1379 0.0265 NA NA NA NA cash
2018-09-11 FALSE SCH2 EOF SCH FBM 0.0930 20 0.1185 1275.0 895.00 FALSE NA NA 5.000 TRUE 4.320 TRUE 0.0397 FALSE 0.4180 TRUE 0.4400 FALSE -0.0437 TRUE 0.4150 13855.000 0.0112 0.0148 17.6651 0.0693 0.0599 38.9445 0.1527 0.1320 4.2702 0.0167 0.0145 NA NA NA NA cash
2018-09-27 FALSE MUZ1 EOF MUZ CCMT 0.0926 40 0.1206 700.0 579.00 FALSE 2.9700 0.7930 3.760 FALSE 3.350 TRUE 0.0802 FALSE 0.5970 TRUE 2.4200 FALSE -0.0377 TRUE 2.3950 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-09-27 FALSE MUZ2 EOF MUZ FBM 0.0940 30 0.1640 2333.3 2596.00 FALSE 3.0700 6.2100 9.280 FALSE 10.900 TRUE 0.7230 FALSE 0.3610 TRUE 0.2380 FALSE -0.0044 TRUE 0.2130 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-09-27 FALSE SCH2 EOF SCH FBM 0.0921 30 0.1149 760.0 926.00 FALSE 3.1200 0.1970 3.320 FALSE 4.230 TRUE 0.2400 FALSE 1.0700 TRUE 1.5100 FALSE 0.0345 TRUE 1.4850 63010.000 0.0511 0.0672 47.8876 0.2092 0.2665 105.5730 0.4612 0.5876 11.5760 0.0506 0.0644 NA NA NA NA cash
2018-09-27 FALSE SIM1 EOF SIM CCMT 0.0932 20 0.1364 2160.0 3536.00 FALSE 6.5800 1.6200 8.200 FALSE 6.810 TRUE 0.6220 FALSE 0.4860 TRUE 3.9900 FALSE 0.1340 TRUE 3.8560 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2018-10-18 TRUE CAR1 EOF CAR CCMT 0.0948 30 0.0979 103.3 179.00 FALSE 3.1000 1.5800 4.680 TRUE 5.700 FALSE 0.2010 TRUE 3.5700 TRUE 3.0700 TRUE -0.0714 FALSE 3.0450 1503586.000 1.2192 0.6543 155.3706 7.0368 8.5704 342.5299 15.5133 18.8944 15.3189 0.6938 0.8450 NA NA NA NA cash
2018-10-18 TRUE MUR1 EOF MUR CCMT 0.0914 30 0.1166 840.0 1544.00 FALSE 10.4000 2.6700 13.000 TRUE 4.070 FALSE 0.1090 TRUE 0.5230 TRUE 9.9100 TRUE -0.0720 FALSE 9.8850 1472029.000 1.1936 0.7523 1236.5044 19.1364 5.9912 2725.9975 42.1881 13.2081 143.1721 2.2158 0.6937 NA NA NA NA cash
2018-10-18 TRUE MUR2 EOF MUR FBM 0.0910 30 0.0990 266.7 387.00 FALSE 16.3000 0.3640 16.700 TRUE 1.330 FALSE 0.0509 TRUE 0.2250 TRUE 13.2000 TRUE -0.0257 FALSE 13.1750 195482.000 0.1585 0.1166 52.1285 3.2645 0.2600 114.9226 7.1970 0.5732 7.1248 0.4462 0.0355 NA NA NA NA cash
2018-10-18 TRUE SIM1 EOF SIM CCMT 0.0943 30 0.0947 13.3 47.50 FALSE 3.2600 0.9370 4.190 TRUE 1.880 FALSE 0.2670 TRUE 1.5100 TRUE 3.4200 TRUE -0.0681 FALSE 3.3950 110230.000 0.0894 0.0751 1.4697 0.4619 0.2072 3.2402 1.0182 0.4569 0.2267 0.0713 0.0320 NA NA NA NA cash
2018-11-04 TRUE CAR1 EOF CAR CCMT 0.0895 45 0.0995 222.2 198.00 FALSE 1.8900 0.2720 2.160 TRUE 0.075 TRUE 0.0286 TRUE 1.7600 TRUE 0.2330 TRUE -0.0591 FALSE 0.2080 458257.000 0.3716 0.1994 101.8349 0.9898 0.0344 224.5052 2.1822 0.0758 10.0405 0.0976 0.0034 NA NA NA NA cover
2018-11-04 TRUE MUR2 EOF MUR FBM 0.0906 20 0.1041 675.0 862.00 FALSE 3.4800 1.9300 5.410 TRUE 3.230 TRUE 0.1110 TRUE 0.1890 TRUE 3.8400 TRUE -0.0711 FALSE 3.8150 1449040.000 1.1749 0.8645 978.1020 7.8393 4.6804 2156.3237 17.2825 10.3184 133.6840 1.0715 0.6397 NA NA NA NA cover
2018-11-04 TRUE SIM1 EOF SIM CCMT 0.0927 50 0.0952 50.0 49.80 FALSE 1.7700 0.1840 1.960 TRUE 0.997 TRUE 0.0738 TRUE 0.4140 TRUE 0.7400 TRUE -0.0672 FALSE 0.7150 401565.000 0.3256 0.2734 20.0783 0.7871 0.4004 44.2645 1.7352 0.8826 3.0976 0.1214 0.0618 NA NA NA NA cover
2018-11-11 TRUE CAR1 EOF CAR CCMT 0.0944 40 0.0957 32.5 143.00 FALSE 1.0100 1.1600 2.180 TRUE 2.970 TRUE 0.1620 FALSE 1.2000 TRUE 0.6330 TRUE -0.0401 FALSE 0.6080 4596368.000 3.7269 2.0001 149.3820 10.0201 13.6512 329.3275 22.0903 30.0955 14.7284 0.9879 1.3460 NA NA NA NA cover
2018-11-11 TRUE MUR1 EOF MUR CCMT 0.0933 30 0.1139 686.7 1020.00 FALSE 2.9000 1.5300 4.430 TRUE 3.460 TRUE 0.1480 FALSE 0.2250 TRUE 1.3700 TRUE -0.0504 FALSE 1.3450 1871639.000 1.5176 0.9565 1285.1921 8.2914 6.4759 2833.3345 18.2791 14.2767 148.8096 0.9600 0.7498 NA NA NA NA cover
2018-11-11 TRUE MUR2 EOF MUR FBM 0.0924 30 0.1595 2236.7 2565.00 FALSE 4.2500 0.2410 4.490 TRUE 4.610 TRUE 0.2280 FALSE 0.2010 TRUE 0.4270 TRUE -0.0517 FALSE 0.4020 868026.000 0.7038 0.5178 1941.4848 3.8974 4.0016 4280.1974 8.5923 8.8219 265.3563 0.5327 0.5469 NA NA NA NA cover
2018-11-11 TRUE SIM1 EOF SIM CCMT 0.0916 40 0.1035 297.5 348.00 FALSE 1.2500 0.8190 2.070 TRUE 1.520 TRUE 0.1310 FALSE 0.2120 TRUE 0.3250 TRUE -0.0472 FALSE 0.3000 78164.000 0.0634 0.0532 23.2538 0.1618 0.1188 51.2653 0.3567 0.2619 3.5875 0.0250 0.0183 NA NA NA NA cover
2018-12-03 TRUE CAR1 EOF CAR CCMT 0.0910 40 0.0926 40.0 33.90 FALSE 4.2500 1.2500 5.500 TRUE 3.010 TRUE 0.1610 FALSE 2.0100 TRUE 2.3700 TRUE -0.0399 FALSE 2.3450 119869.000 0.0972 0.0522 4.7948 0.6593 0.3608 10.5705 1.4534 0.7954 0.4727 0.0650 0.0356 NA NA NA NA cover
2018-12-03 TRUE MUR1 EOF MUR CCMT 0.0926 40 0.1122 490.0 648.00 FALSE 2.5200 1.2800 3.800 TRUE 2.280 TRUE 0.2110 FALSE 0.2860 TRUE 0.7240 TRUE -0.0409 FALSE 0.6990 245272.000 0.1989 0.1253 120.1833 0.9320 0.5592 264.9561 2.0548 1.2329 13.9158 0.1079 0.0648 NA NA NA NA cover
2018-12-03 TRUE SCH2 EOF SCH FBM 0.0920 20 0.1746 4130.0 6032.00 FALSE 7.8400 5.0600 12.900 TRUE 18.200 TRUE 0.3050 FALSE 1.2000 TRUE 0.6330 TRUE -0.0379 FALSE 0.6080 1013721.000 0.8220 1.0815 4186.6677 13.0770 18.4497 9229.9277 28.8296 40.6743 1012.0535 3.1611 4.4599 NA NA NA NA cover
2018-12-11 FALSE CAR1 EOF CAR CCMT 0.0916 45 0.0928 26.7 31.90 FALSE 0.5720 1.6700 2.240 TRUE 2.090 TRUE 0.1610 FALSE 0.9700 FALSE 0.2670 FALSE -0.0350 FALSE 0.2420 4760333.000 3.8599 2.0715 126.9422 10.6631 9.9491 279.8568 23.5080 21.9338 12.5160 1.0513 0.9809 NA NA NA NA cover
2018-12-11 FALSE MUR1 EOF MUR CCMT 0.0917 30 0.1024 356.7 479.00 FALSE 1.0600 4.2800 5.340 TRUE 2.030 TRUE 0.0390 FALSE 0.2580 FALSE 3.8800 FALSE -0.0331 FALSE 3.8550 4470902.000 3.6252 2.2848 1594.6217 23.8746 9.0759 3515.5030 52.6340 20.0088 184.6378 2.7644 1.0509 NA NA NA NA cover
2018-12-11 FALSE MUR2 EOF MUR FBM 0.0918 30 0.1134 720.0 1004.00 FALSE 1.6900 2.2100 3.900 TRUE 3.140 TRUE -0.0236 FALSE 0.2210 FALSE 0.9440 FALSE -0.0255 FALSE 0.9190 2739316.000 2.2211 1.6342 1972.3075 10.6833 8.6015 4348.1492 23.5525 18.9628 269.5691 1.4602 1.1756 NA NA NA NA cover
2019-01-16 FALSE CAR1 EOF CAR CCMT 0.0927 50 0.0938 22.0 33.20 FALSE 0.8550 0.7340 1.590 TRUE 2.370 TRUE 0.3590 TRUE 0.9450 TRUE 0.2410 TRUE -0.4350 FALSE 0.2160 932079.000 0.7558 0.4056 20.5057 1.4820 2.2090 45.2069 3.2672 4.8700 2.0218 0.1461 0.2178 NA NA NA NA cover
2019-01-16 FALSE MUR1 EOF MUR CCMT 0.0919 20 0.1285 1830.0 2252.00 FALSE 2.0300 1.5100 3.540 TRUE 5.510 TRUE 0.0296 TRUE 0.1810 TRUE 0.3710 TRUE -0.4360 FALSE 0.3460 571585.000 0.4635 0.2921 1046.0005 2.0234 3.1494 2306.0128 4.4608 6.9432 121.1141 0.2343 0.3647 NA NA NA NA cover
2019-01-16 FALSE MUR2 EOF MUR FBM 0.0919 35 0.1288 1054.3 1680.00 FALSE 1.9700 0.5370 2.510 TRUE 4.100 TRUE 0.2670 TRUE 0.1200 TRUE 0.3700 TRUE -0.4460 FALSE 0.3450 127275.000 0.1032 0.0759 134.1842 0.3195 0.5218 295.8225 0.7043 1.1504 18.3399 0.0437 0.0713 NA NA NA NA cover
2019-01-21 TRUE CAR1 EOF CAR CCMT 0.0914 40 0.0939 62.5 70.40 FALSE 0.3530 1.9300 2.280 TRUE 2.110 TRUE 0.3680 TRUE 1.0000 TRUE 0.6540 TRUE -0.4430 FALSE 0.6290 1412468.000 1.1453 0.6146 88.2792 3.2204 2.9803 194.6204 7.0998 6.5704 8.7040 0.3175 0.2938 NA NA NA NA cover
2019-01-21 TRUE MUR1 EOF MUR CCMT 0.0921 20 0.1145 1120.0 1780.00 FALSE 3.1800 0.6780 3.860 TRUE 5.040 TRUE 0.1320 TRUE 0.1580 TRUE 0.5550 TRUE -0.4380 FALSE 0.5300 1929384.000 1.5644 0.9860 2160.9101 7.4474 9.7241 4763.9424 16.4186 21.4377 250.2071 0.8623 1.1259 NA NA NA NA cover
2019-01-21 TRUE MUR2 EOF MUR FBM 0.0923 20 0.1266 1715.0 2370.00 FALSE 3.7100 0.0520 3.760 TRUE 6.250 TRUE 0.1700 TRUE 0.1810 TRUE 0.3350 TRUE -0.4320 FALSE 0.3100 1613370.000 1.3082 0.9625 2766.9295 6.0663 10.0836 6099.9729 13.3737 22.2302 378.1756 0.8291 1.3782 NA NA NA NA cover
2019-01-21 TRUE SCH2 EOF SCH FBM 0.0908 20 0.1050 710.0 857.00 FALSE 1.7300 1.2400 2.970 TRUE 5.330 TRUE 0.5760 TRUE 1.0300 TRUE 0.2480 TRUE -0.4460 FALSE 0.2230 621133.000 0.5036 0.6627 441.0044 1.8448 3.3106 972.2384 4.0670 7.2986 106.6051 0.4459 0.8003 NA NA NA NA cover
2019-01-25 TRUE CAR1 EOF CAR CCMT 0.0929 40 0.0930 2.5 14.80 FALSE NA NA NA FALSE 1.350 TRUE 0.0498 FALSE 0.3860 TRUE 0.0035 TRUE -0.2590 FALSE -0.0215 661290.000 0.5362 0.2878 1.6532 NA 0.8927 3.6447 NA 1.9681 0.1630 NA 0.0880 NA NA NA NA cover
2019-01-25 TRUE MUR1 EOF MUR CCMT 0.0931 20 0.1110 895.0 1290.00 FALSE NA NA NA FALSE 4.220 TRUE -0.4880 FALSE 0.0863 TRUE 0.0035 TRUE -0.2670 FALSE -0.0215 2214182.000 1.7953 1.1315 1981.6929 NA 9.3438 4368.8401 NA 20.5994 229.4559 NA 1.0819 NA NA NA NA cover
2019-01-25 TRUE MUR2 EOF MUR FBM 0.0910 20 0.1090 900.0 1610.00 FALSE NA NA NA FALSE 4.980 TRUE -0.5240 FALSE 0.0888 TRUE 0.0035 TRUE -0.2600 FALSE -0.0215 894271.000 0.7251 0.5335 804.8439 NA 4.4535 1774.3589 NA 9.8181 110.0036 NA 0.6087 NA NA NA NA cover
2019-03-06 TRUE CAR1 EOF CAR CCMT 0.0949 41 0.1091 346.3 205.00 FALSE NA NA NA FALSE 2.510 FALSE -0.1000 FALSE 0.2400 FALSE 0.0035 TRUE -0.0133 TRUE -0.0215 954810.000 0.7742 0.4155 330.6903 NA 2.3966 729.0398 NA 5.2835 32.6046 NA 0.2363 NA NA NA NA cover
2019-03-06 TRUE CAR2 EOF CAR FBM 0.0940 40 0.1078 345.0 243.00 FALSE NA NA NA FALSE 2.210 FALSE -0.0990 FALSE 0.2470 FALSE 0.0035 TRUE -0.0236 TRUE -0.0215 904735.000 0.7336 0.3762 312.1336 NA 1.9995 688.1297 NA 4.4080 29.4073 NA 0.1884 NA NA NA NA cover
2019-03-06 TRUE MUR1 EOF MUR CCMT 0.0921 40 0.2208 3217.5 4005.00 FALSE NA NA NA FALSE 9.970 FALSE -0.1380 FALSE 0.0523 FALSE 0.0035 TRUE -0.0230 TRUE -0.0215 1258372.000 1.0203 0.6431 4048.8119 NA 12.5460 8926.0107 NA 27.6588 468.8031 NA 1.4527 NA NA NA NA cover
2019-03-06 TRUE MUR2 EOF MUR FBM 0.0937 40 0.1785 2120.0 2895.00 FALSE NA NA NA FALSE 6.700 FALSE -0.1260 FALSE 0.0685 FALSE 0.0035 TRUE -0.0232 TRUE -0.0215 928919.000 0.7532 0.5542 1969.3083 NA 6.2238 4341.5370 NA 13.7209 269.1591 NA 0.8506 NA NA NA NA cover
2019-03-06 TRUE SIM1 EOF SIM CCMT 0.0939 41 0.1001 151.2 178.00 FALSE NA NA NA FALSE 8.739 FALSE -0.0826 FALSE 0.0532 FALSE 0.0035 TRUE -0.0231 TRUE -0.0215 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2019-03-12 TRUE HB INST NA NA 0.0925 40 0.0979 135.0 246.00 TRUE 1.3900 0.8090 2.200 TRUE 1.390 TRUE -0.0746 FALSE 0.1540 FALSE -0.2010 TRUE -0.0204 TRUE -0.2025 NA NA NA NA NA NA NA NA NA NA NA NA 8.87 83.5 603.8 13.1 cover
2019-03-12 TRUE PB INST NA NA 0.0941 41 0.1037 234.1 367.00 TRUE 1.2500 0.0917 2.160 TRUE 1.820 TRUE 0.3650 FALSE 0.1070 FALSE -0.1980 TRUE -0.0150 TRUE -0.1995 NA NA NA NA NA NA NA NA NA NA NA NA 8.53 92.3 444.7 19.5 cover
2019-03-16 TRUE MUR1 EOF MUR CCMT 0.0942 30 0.2518 5253.3 7905.00 TRUE 8.3900 3.9800 12.400 TRUE 17.000 TRUE -0.0571 FALSE 0.1980 FALSE 0.1330 TRUE -0.0172 TRUE 0.1080 570675.000 0.4627 0.2916 2997.9460 7.0764 9.7015 6609.2718 15.6006 21.3879 347.1256 0.8194 1.1233 NA NA NA NA cover
2019-03-16 TRUE MUR2 EOF MUR FBM 0.0922 20 0.2203 6405.0 10320.00 TRUE 9.8400 4.5100 14.300 TRUE 21.200 TRUE -0.0071 FALSE 0.1820 FALSE 0.0652 TRUE -0.0166 TRUE 0.0402 727044.000 0.5895 0.4337 4656.7168 10.3967 15.4133 10266.1979 22.9206 33.9802 636.4661 1.4210 2.1066 NA NA NA NA cover
2019-03-16 TRUE SCH2 EOF SCH FBM 0.0934 30 0.4157 10743.3 7845.00 TRUE 9.2700 8.4500 17.700 TRUE 27.500 TRUE -0.0689 FALSE 0.4680 FALSE 0.5180 TRUE -0.0177 TRUE 0.4930 856007.000 0.6941 0.9133 9196.3685 15.1513 23.5402 20274.3141 33.4026 51.8967 2223.0608 3.6626 5.6904 NA NA NA NA cover
2019-03-16 TRUE SIM1 EOF SIM CCMT 0.0934 40 0.1376 1105.0 1377.00 TRUE 2.3400 2.1700 4.510 TRUE 4.610 TRUE 0.0113 FALSE 0.0503 FALSE 0.1210 TRUE -0.0166 TRUE 0.0960 146494.000 0.1188 0.0997 161.8759 0.6607 0.6753 356.8715 1.4566 1.4888 24.9735 0.1019 0.1042 NA NA NA NA cover
2019-03-26 TRUE CAR2 EOF CAR FBM 0.0899 24 0.2919 8416.7 8100.00 TRUE 9.7000 9.1000 18.800 TRUE 24.100 TRUE 0.2930 FALSE 1.2300 FALSE 2.4900 TRUE -0.0124 TRUE 2.4650 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2019-03-26 TRUE HB INST NA NA 0.0912 50 0.0964 104.0 179.00 TRUE 1.8000 0.4120 2.220 TRUE 1.290 TRUE -0.0048 FALSE 0.1400 FALSE 1.2200 TRUE -0.0148 TRUE 1.2185 NA NA NA NA NA NA NA NA NA NA NA NA 8.52 81.5 209.3 13.8 cover
2019-03-26 TRUE MUR1 EOF MUR CCMT 0.0928 24 0.1315 1612.5 2085.00 TRUE 2.6300 2.8400 5.470 TRUE 5.830 TRUE 0.0817 FALSE 0.4590 FALSE 0.5240 TRUE -0.0162 TRUE 0.4990 477748.000 0.3874 0.2441 770.3686 2.6133 2.7853 1698.3547 5.7612 6.1404 89.1993 0.3026 0.3225 NA NA NA NA cover
2019-03-26 TRUE MUR2 EOF MUR FBM 0.0913 30 0.1731 2726.7 3405.00 TRUE 3.0500 6.0900 9.150 TRUE 6.990 TRUE 0.0689 FALSE 0.3720 FALSE 0.6460 TRUE -0.0173 TRUE 0.6210 243758.000 0.1976 0.1454 664.6468 2.2304 1.7039 1465.2804 4.9171 3.7563 90.8419 0.3048 0.2329 NA NA NA NA cover
2019-03-26 TRUE PB INST NA NA 0.0944 50 0.1078 268.0 472.00 TRUE 1.9200 1.2600 3.170 TRUE 2.560 TRUE 0.3710 FALSE 0.1530 FALSE 1.0200 TRUE -0.0145 TRUE 1.0185 NA NA NA NA NA NA NA NA NA NA NA NA 7.98 77.3 1457.7 14.4 cover
2019-03-26 TRUE SCH2 EOF SCH FBM 0.0914 32 0.1346 1350.0 1845.00 TRUE 2.9000 2.0300 4.930 TRUE 10.700 TRUE 4.4200 FALSE 0.7200 FALSE 0.4930 TRUE -0.0164 TRUE 0.4680 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2019-03-26 TRUE SIM1 EOF SIM CCMT 0.0908 30 0.1029 403.3 340.00 TRUE 2.5300 1.0300 3.550 TRUE 2.230 TRUE 0.2890 FALSE 0.3470 FALSE 2.7900 TRUE -0.0161 TRUE 2.7650 151764.000 0.1231 0.1033 61.2115 0.5388 0.3384 134.9468 1.1878 0.7461 9.4434 0.0831 0.0522 NA NA NA NA cover
2019-04-05 TRUE HB INST NA NA 0.0914 55 0.0973 107.3 57.60 TRUE 1.3200 0.2160 1.530 TRUE 0.846 FALSE 0.3250 FALSE 0.4960 TRUE 0.8230 TRUE -0.0192 TRUE 0.8215 NA NA NA NA NA NA NA NA NA NA NA NA 8.94 100.2 68.0 21.0 cover
2019-04-05 TRUE PB INST NA NA 0.0906 50 0.1130 448.0 698.00 TRUE 3.2800 0.5290 3.810 TRUE 3.040 FALSE 0.1320 FALSE 0.3660 TRUE 2.2300 TRUE -0.0129 TRUE 2.2285 NA NA NA NA NA NA NA NA NA NA NA NA 7.93 81.7 716.9 16.9 cover
2019-04-06 TRUE CAR1 EOF CAR CCMT 0.0916 35 0.1391 1357.1 1176.00 TRUE 4.4700 4.4500 8.920 TRUE 8.444 FALSE -0.0009 FALSE 0.8090 TRUE 2.0900 TRUE -0.0245 TRUE 2.0650 157406.000 0.1276 0.0685 213.6224 1.4041 1.3291 470.9520 3.0954 2.9302 21.0623 0.1384 0.1310 NA NA NA NA cover
2019-04-06 TRUE CAR2 EOF CAR FBM 0.0917 40 0.1932 2537.5 2130.00 TRUE 6.4300 2.4300 8.860 TRUE 9.920 FALSE 0.5470 FALSE 0.9630 TRUE 4.2900 TRUE 0.0457 TRUE 4.2650 163006.000 0.1322 0.0678 413.6277 1.4442 1.6170 911.8837 3.1840 3.5649 38.9694 0.1361 0.1523 NA NA NA NA cover
2019-04-06 TRUE MUR1 EOF MUR CCMT 0.0892 30 0.1290 1326.7 1352.00 TRUE 2.8600 0.5610 3.420 TRUE 5.960 FALSE -0.0031 FALSE 0.2010 TRUE 0.4300 TRUE -0.0324 TRUE 0.4050 1312552.000 1.0643 0.6708 1741.3190 4.4889 7.8228 3838.9118 9.8963 17.2462 201.6235 0.5198 0.9058 NA NA NA NA cover
2019-04-06 TRUE MUR2 EOF MUR FBM 0.0891 35 0.1870 2797.1 3105.00 TRUE 5.3100 -0.5600 4.750 TRUE 7.460 FALSE -0.0084 FALSE 0.1340 TRUE 1.3900 TRUE -0.0105 TRUE 1.3650 981228.000 0.7956 0.5854 2744.6349 4.6608 7.3200 6050.8221 10.2753 16.1376 375.1285 0.6370 1.0005 NA NA NA NA cover
2019-04-06 TRUE SCH2 EOF SCH FBM 0.0911 30 0.1191 933.3 674.00 TRUE 2.1700 8.0100 10.200 TRUE 8.120 FALSE 3.3000 FALSE 1.4600 TRUE 0.8580 TRUE -0.0223 TRUE 0.8330 511082.000 0.4144 0.5453 477.0099 5.2130 4.1500 1051.6160 11.4927 9.1491 115.3088 1.2602 1.0032 NA NA NA NA cover
2019-04-06 TRUE SIM1 EOF SIM CCMT 0.0902 45 0.1370 1040.0 986.00 TRUE 3.2300 0.9380 4.170 TRUE 3.520 FALSE 0.1100 FALSE 0.1120 TRUE 1.6500 TRUE -0.0181 TRUE 1.6250 563390.000 0.4568 0.3836 585.9256 2.3493 1.9831 1291.7316 5.1793 4.3720 90.3941 0.3624 0.3059 NA NA NA NA cover
2019-04-08 TRUE HB INST NA NA 0.0908 39 0.0978 179.5 233.00 TRUE 0.6080 0.3870 0.994 TRUE 1.160 TRUE -0.0335 FALSE 0.1160 TRUE 0.0511 TRUE -0.0259 TRUE 0.0496 NA NA NA NA NA NA NA NA NA NA NA NA 8.99 96.4 213.9 18.5 cover
2019-04-08 TRUE PB INST NA NA 0.0913 35 0.1398 1385.7 2280.00 TRUE 3.6100 2.2700 5.880 TRUE 3.810 TRUE 0.0185 FALSE 0.1040 TRUE 0.9420 TRUE -0.0179 TRUE 0.9405 NA NA NA NA NA NA NA NA NA NA NA NA 8.84 93.8 2301.0 17.9 cover
2019-04-10 TRUE CAR2 EOF CAR FBM 0.0902 20 0.1557 3275.0 4020.00 TRUE 5.6000 3.8600 9.470 TRUE 13.900 TRUE 0.0088 FALSE 0.2600 TRUE 0.9850 TRUE -0.0106 TRUE 0.9600 3285448.000 2.6640 1.3661 10759.8422 31.1132 45.6677 23721.1481 68.5921 100.6791 1013.7243 2.9313 4.3025 NA NA NA NA cover
2019-04-10 TRUE MUR1 EOF MUR CCMT 0.0897 21 0.1821 4400.0 6170.00 TRUE 5.6600 3.9200 9.590 TRUE 11.100 TRUE 0.0172 FALSE 0.1280 TRUE 0.1590 TRUE 0.1210 TRUE 0.0380 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2019-04-10 TRUE MUR2 EOF MUR FBM 0.0911 20 0.1967 5280.0 9780.00 TRUE 7.9800 4.0100 12.000 TRUE 9.560 TRUE -0.0319 FALSE 0.1500 TRUE 0.3640 TRUE -0.0236 TRUE 0.3390 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2019-04-10 TRUE SCH2 EOF SCH FBM 0.0906 45 0.1177 602.2 919.00 TRUE 2.5700 5.4900 8.060 TRUE 3.750 TRUE 2.5400 FALSE 0.4530 TRUE 1.2500 TRUE 0.0131 TRUE 1.2250 1190294.000 0.9651 1.2699 716.8215 9.5938 4.4636 1580.3047 21.1504 9.8405 173.2790 2.3191 1.0790 NA NA NA NA cover
2019-04-10 TRUE SIM1 EOF SIM CCMT 0.0923 40 0.1142 547.5 826.00 TRUE 1.5100 1.0800 2.590 TRUE 2.510 TRUE 0.6060 FALSE 2.1500 TRUE 0.0240 TRUE -0.0401 TRUE -0.0010 4339433.000 3.5186 2.9547 2375.8396 11.2391 10.8920 5237.7759 24.7778 24.0125 366.5344 1.7339 1.6804 NA NA NA NA cover
2019-04-26 TRUE HB INST NA NA 0.0905 50 0.0953 96.0 126.00 TRUE 1.2500 0.3210 1.570 TRUE 1.690 FALSE 0.1740 TRUE 0.5420 TRUE 0.6470 TRUE -0.0117 TRUE 0.6455 NA NA NA NA NA NA NA NA NA NA NA NA 8.47 90.2 173.7 18.5 cover
2019-04-27 TRUE CAR1 EOF CAR CCMT 0.0894 50 0.0942 96.0 72.00 TRUE 13.4000 3.4600 16.800 TRUE 1.200 FALSE 2.6100 TRUE 0.0798 TRUE 11.3000 TRUE 0.1690 TRUE 11.1310 1419139.000 1.1507 0.6175 136.2373 23.8415 1.7030 300.3488 52.5610 3.7544 13.4324 2.3507 0.1679 NA NA NA NA cover
2019-04-27 TRUE MUR1 EOF MUR CCMT 0.0896 50 0.1877 1962.0 2430.00 TRUE 4.5300 1.3000 5.830 TRUE 7.550 FALSE 0.1000 TRUE 0.1530 TRUE 1.1300 TRUE -0.0127 TRUE 1.1050 195761.000 0.1587 0.1000 384.0831 1.1413 1.4780 846.7496 2.5161 3.2584 44.4721 0.1321 0.1711 NA NA NA NA cover
2019-04-27 TRUE MUR2 EOF MUR FBM 0.0914 50 0.1932 2036.0 3015.00 TRUE 4.6400 -0.4360 4.200 TRUE 5.440 FALSE 0.0163 TRUE 0.1470 TRUE 0.6870 TRUE -0.0190 TRUE 0.6620 40259.000 0.0326 0.0240 81.9673 0.1691 0.2190 180.7052 0.3728 0.4828 11.2030 0.0231 0.0299 NA NA NA NA cover
2019-04-27 TRUE SCH2 EOF SCH FBM 0.0904 50 0.1197 586.0 472.50 TRUE 2.2800 0.9990 3.280 TRUE 3.560 FALSE 0.6620 TRUE 0.4660 TRUE 1.2500 TRUE -0.0116 TRUE 1.2250 854956.000 0.6932 0.9121 501.0042 2.8043 3.0436 1104.5139 6.1823 6.7100 121.1090 0.6779 0.7357 NA NA NA NA cover
2019-04-27 TRUE SIM1 EOF SIM CCMT 0.0905 50 0.1124 438.0 508.50 TRUE 2.9000 0.6570 3.560 TRUE 1.510 FALSE 0.1770 TRUE 0.0692 TRUE 1.8000 TRUE -0.0095 TRUE 1.7750 124262.000 0.1008 0.0846 54.4268 0.4424 0.1876 119.9892 0.9753 0.4137 8.3967 0.0682 0.0289 NA NA NA NA cover
2019-05-07 TRUE ARR1 EOF ARR CCMT 0.0912 41 0.1222 756.1 811.50 TRUE 9.3300 3.7800 13.100 TRUE 3.640 TRUE 5.2100 TRUE 0.0960 TRUE 8.6200 TRUE 0.2400 TRUE 8.3800 601610.000 0.4878 0.4023 454.8759 7.8811 2.1899 1002.8193 17.3747 4.8278 68.9223 1.1941 0.3318 NA NA NA NA cash
2019-05-07 TRUE CAR1 EOF CAR CCMT 0.0928 40 0.0981 132.5 77.40 TRUE 1.9000 0.6770 2.580 TRUE 1.280 TRUE 0.1350 TRUE 0.1850 TRUE 1.4300 TRUE -0.0116 TRUE 1.4050 2274674.000 1.8444 0.9898 301.3943 5.8687 2.9116 664.4539 12.9380 6.4189 29.7162 0.5786 0.2871 NA NA NA NA cash
2019-05-07 TRUE MUR1 EOF MUR CCMT 0.0923 40 0.1308 962.5 1014.00 TRUE 5.4300 0.9470 6.380 TRUE 4.430 TRUE 0.0180 TRUE 0.2690 TRUE 3.6400 TRUE -0.0123 TRUE 3.6150 1351920.000 1.0962 0.6909 1301.2230 8.6252 5.9890 2868.6762 19.0152 13.2034 150.6658 0.9987 0.6935 NA NA NA NA cash
2019-05-07 TRUE MUR2 EOF MUR FBM 0.0903 20 0.1070 835.0 1021.50 TRUE 5.5800 0.7390 6.320 TRUE 3.900 TRUE 0.0228 TRUE 0.1540 TRUE 3.8200 TRUE -0.0112 TRUE 3.7950 851307.000 0.6903 0.5079 710.8413 5.3803 3.3201 1567.1208 11.8613 7.3195 97.1557 0.7354 0.4538 NA NA NA NA cash
2019-05-07 TRUE PBR1 EOF PBR CCMT 0.0929 30 0.2148 4063.3 1965.00 TRUE 2.5700 3.0800 5.650 TRUE 7.550 TRUE 0.3630 TRUE 0.1690 TRUE 0.3780 TRUE -0.0166 TRUE 0.3765 173089.000 0.1403 0.0321 703.3183 0.9780 1.3068 1550.5355 2.1560 2.8810 29.5960 0.0412 0.0550 NA NA NA NA cash
2019-05-07 TRUE SCH2 EOF SCH FBM 0.0906 40 0.1213 767.5 765.00 TRUE 2.1800 1.0300 3.210 TRUE 3.790 TRUE 0.9300 TRUE 0.5370 TRUE 1.1600 TRUE -0.0040 TRUE 1.1350 949065.000 0.7695 1.0126 728.4074 3.0465 3.5970 1605.8469 6.7163 7.9298 176.0797 0.7364 0.8695 NA NA NA NA cash
2019-05-20 TRUE PB INST NA NA 2.6672 30 2.6768 320.0 591.00 TRUE 0.9880 0.4960 1.480 TRUE 2.080 TRUE 0.2940 TRUE 0.1180 TRUE 0.2740 TRUE -0.0062 TRUE 0.2725 NA NA NA NA NA NA NA NA NA NA NA NA 6.28 84.8 617.5 31.1 cash
2019-05-21 TRUE ARR1 EOF ARR CCMT 2.7095 30 2.7526 1436.7 1670.00 TRUE 4.2500 5.5400 9.790 TRUE 2.080 TRUE 3.2800 TRUE 0.0470 TRUE 2.5900 TRUE 0.0544 TRUE 2.5356 150449.000 0.1220 0.1006 216.1451 1.4729 0.3129 476.5134 3.2471 0.6899 32.7501 0.2232 0.0474 NA NA NA NA cash
2019-05-21 TRUE CAR1 EOF CAR CCMT 2.6715 50 2.6785 140.0 181.00 TRUE 2.4500 2.9600 5.410 TRUE 4.010 TRUE 0.9770 TRUE 1.2600 TRUE 1.2300 TRUE 0.0694 TRUE 1.1606 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-05-21 TRUE PBR1 EOF PBR CCMT 2.6259 30 2.6478 730.0 554.00 TRUE 2.6200 0.6680 3.290 TRUE 2.830 TRUE 1.2700 TRUE 0.0641 TRUE 2.0300 TRUE 0.1160 TRUE 1.9140 106340.000 0.0862 0.0197 77.6282 0.3499 0.3009 171.1391 0.7713 0.6635 3.2666 0.0147 0.0127 NA NA NA NA cash
2019-05-21 TRUE SCH1 EOF SCH CCMT 2.6803 30 2.6868 216.7 245.00 TRUE 12.4000 169.0000 181.000 TRUE 2.540 TRUE 10.3000 TRUE 0.5670 TRUE 9.4000 TRUE 0.0435 TRUE 9.3750 42361.000 0.0343 0.0397 9.1782 7.6673 0.1076 20.2343 16.9034 0.2372 1.9494 1.6285 0.0229 NA NA NA NA cash
2019-05-21 TRUE SCH2 EOF SCH FBM 2.7034 20 2.7063 145.0 111.00 TRUE 3.1500 45.5000 48.600 TRUE 2.860 TRUE 5.6600 TRUE 0.9940 TRUE 3.5700 TRUE 0.0435 TRUE 3.5450 32708.000 0.0265 0.0349 4.7427 1.5896 0.0935 10.4557 3.5045 0.2062 1.1465 0.3843 0.0226 NA NA NA NA cash
2019-05-21 TRUE SIM1 EOF SIM CCMT 2.6999 50 2.9117 4236.0 3850.00 TRUE 4.9500 1.1000 6.050 TRUE 9.660 TRUE 0.4810 TRUE 0.0253 TRUE 1.1300 TRUE 0.0129 TRUE 1.1050 720789.000 0.5844 0.4908 3053.2622 4.3608 6.9628 6731.2219 9.6138 15.3502 471.0442 0.6728 1.0742 NA NA NA NA cash
2019-05-21 TRUE SIM2 EOF SIM FBM 2.7109 50 2.8804 3390.0 4040.00 TRUE 4.0900 4.3300 8.420 TRUE 7.430 TRUE 1.9800 TRUE 0.0048 TRUE 0.5560 TRUE 0.0032 TRUE 0.5310 1313953.000 1.0654 0.7268 4454.3007 11.0635 9.7627 9819.9513 24.3906 21.5228 558.2690 1.3866 1.2236 NA NA NA NA cash
2019-06-04 TRUE ARR2 EOF ARR FBM 0.0910 40 0.1368 1145.0 835.00 TRUE 2.6900 5.1200 7.810 TRUE 4.320 TRUE 2.3000 TRUE 0.2110 TRUE 1.9700 TRUE 0.1310 TRUE 1.8390 122747.000 0.0995 0.0772 140.5453 0.9587 0.5303 309.8462 2.1134 1.1690 20.0159 0.1365 0.0755 NA NA NA NA cash
2019-06-04 TRUE PBR1 EOF PBR CCMT 0.0913 40 0.1044 327.5 132.00 TRUE 0.6710 1.9700 2.640 TRUE 3.080 TRUE 0.8770 TRUE 0.9310 TRUE 0.4310 TRUE 0.0025 TRUE 0.4295 274433.000 0.2225 0.0510 89.8768 0.7245 0.8453 198.1424 1.5972 1.8634 3.7821 0.0305 0.0356 NA NA NA NA cash
2019-06-04 TRUE PBR2 EOF PBR FBM 0.0929 40 0.1256 817.5 262.00 TRUE 0.5950 2.2800 2.880 TRUE 2.210 TRUE 0.3340 TRUE 0.1560 TRUE 0.2190 TRUE -0.0012 TRUE 0.2175 4948.000 0.0040 0.0020 4.0450 0.0143 0.0109 8.9176 0.0314 0.0241 0.3733 0.0013 0.0010 NA NA NA NA cash
2019-06-04 TRUE SCH2 EOF SCH FBM 0.0909 40 0.0992 207.5 92.10 TRUE 3.1400 3.3500 6.490 TRUE 1.730 TRUE 3.6900 TRUE 0.3810 TRUE 2.9300 TRUE 0.2020 TRUE 2.7280 798752.000 0.6477 0.8522 165.7410 5.1839 1.3818 365.3927 11.4284 3.0464 40.0650 1.2531 0.3340 NA NA NA NA cash
2019-06-09 TRUE ARR1 EOF ARR CCMT 0.0933 40 0.1108 437.5 290.00 TRUE 12.4000 1.7800 14.200 TRUE 1.720 TRUE 2.9100 TRUE 0.0342 TRUE 11.5000 TRUE 0.1430 TRUE 11.3570 767239.000 0.6221 0.5131 335.6671 10.8948 1.3197 740.0116 24.0187 2.9093 50.8599 1.6508 0.2000 NA NA NA NA cash
2019-06-09 TRUE ARR2 EOF ARR FBM 0.0928 40 0.1098 425.0 291.00 TRUE 13.1000 1.2800 14.400 TRUE 1.570 TRUE 1.9500 TRUE 0.0528 TRUE 11.8000 TRUE 0.0831 TRUE 11.7169 829225.000 0.6724 0.5212 352.4206 11.9408 1.3019 776.9465 26.3248 2.8701 50.1903 1.7006 0.1854 NA NA NA NA cash
2019-06-09 TRUE PBR1 EOF PBR CCMT 0.0941 40 0.1024 207.5 82.40 TRUE 1.2500 3.0400 4.290 TRUE 1.780 TRUE 0.6470 TRUE 0.3310 TRUE 1.2200 TRUE 0.1590 TRUE 1.0610 53684.000 0.0435 0.0100 11.1394 0.2303 0.0956 24.5580 0.5077 0.2107 0.4688 0.0097 0.0040 NA NA NA NA cash
2019-06-09 TRUE PBR2 EOF PBR FBM 0.0913 40 0.1016 257.5 66.20 TRUE 0.6110 2.3600 2.970 TRUE 1.360 TRUE 0.3370 TRUE 0.1370 TRUE 0.4880 TRUE 0.0282 TRUE 0.4598 34117.000 0.0277 0.0139 8.7851 0.1013 0.0464 19.3677 0.2234 0.1023 0.8107 0.0094 0.0043 NA NA NA NA cash
2019-06-09 TRUE SCH1 EOF SCH CCMT 0.0911 40 0.0925 35.0 51.50 TRUE 36.5000 39.1000 75.600 TRUE 1.750 TRUE 16.3000 TRUE 0.5280 TRUE 30.9000 TRUE 0.2410 TRUE 30.6590 294351.000 0.2387 0.2759 10.3023 22.2529 0.5151 22.7124 49.0588 1.1356 2.1881 4.7263 0.1094 NA NA NA NA cash
2019-06-09 TRUE SCH2 EOF SCH FBM 0.0917 40 0.0983 165.0 123.00 TRUE 12.6000 30.7000 43.200 TRUE 3.010 TRUE 10.3000 TRUE 0.9640 TRUE 10.7000 TRUE 0.1370 TRUE 10.5630 859837.000 0.6972 0.9174 141.8731 37.1450 2.5881 312.7734 81.8898 5.7057 34.2953 8.9791 0.6256 NA NA NA NA cash
2019-06-09 TRUE SIM1 EOF SIM CCMT 0.0935 40 0.2599 4160.0 1270.00 TRUE 4.4500 1.6700 6.110 TRUE 3.830 TRUE 0.4350 TRUE 0.0525 TRUE 2.6400 TRUE 0.0037 TRUE 2.6150 13116.000 0.0106 0.0089 54.5626 0.0801 0.0502 120.2886 0.1767 0.1107 8.4177 0.0124 0.0077 NA NA NA NA cash
2019-06-09 TRUE SIM2 EOF SIM FBM 0.0922 40 0.3288 5915.0 6690.00 TRUE 6.0600 0.7220 6.780 TRUE 13.600 TRUE 0.0797 TRUE 0.0306 TRUE 0.6420 TRUE -0.0138 TRUE 0.6170 1127.000 0.0009 0.0006 6.6662 0.0076 0.0153 14.6963 0.0168 0.0338 0.8355 0.0010 0.0019 NA NA NA NA cash
2019-06-18 TRUE MUR1 EOF MUR CCMT 0.0927 40 0.3270 5857.5 9530.00 TRUE 10.7000 4.2100 14.900 TRUE 19.400 TRUE 0.0791 TRUE 0.3620 TRUE 2.6100 TRUE -0.0144 TRUE 2.5850 20980.000 0.0170 0.0107 122.8904 0.3126 0.4070 270.9241 0.6892 0.8973 14.2292 0.0362 0.0471 NA NA NA NA cash
2019-06-18 TRUE MUR2 EOF MUR FBM 0.0944 40 0.3342 5995.0 8350.00 TRUE 10.7000 3.9600 14.600 TRUE 20.400 TRUE 0.0910 TRUE 0.2660 TRUE 3.4700 TRUE -0.0113 TRUE 3.4450 10085.000 0.0082 0.0060 60.4596 0.1472 0.2057 133.2892 0.3246 0.4536 8.2634 0.0201 0.0281 NA NA NA NA cash
2019-06-18 TRUE PB INST NA NA 0.0929 45 0.1100 380.0 820.00 TRUE 2.6000 2.6800 5.290 TRUE 2.880 TRUE 1.1500 TRUE 0.2390 TRUE 1.1700 TRUE 0.0029 TRUE 1.1685 NA NA NA NA NA NA NA NA NA NA NA NA 5.77 75.1 715.5 28.8 cash
2019-06-18 TRUE PBR2 EOF PBR FBM 0.0950 20 0.0945 -25.0 11.00 TRUE 0.3350 1.2600 1.600 TRUE 0.638 TRUE 0.2000 TRUE 0.0264 TRUE 0.0709 TRUE -0.0158 TRUE 0.0694 11794.000 0.0096 0.0048 -0.2948 0.0189 0.0075 -0.6500 0.0416 0.0166 -0.0272 0.0017 0.0007 NA NA NA NA cash
2019-06-20 TRUE CAR1 EOF CAR CCMT 0.0937 35 0.1000 180.0 203.00 TRUE 2.3900 1.9300 4.320 TRUE 2.080 TRUE 0.3120 TRUE 0.4070 TRUE 1.8000 TRUE 0.0129 TRUE 1.7750 512277.000 0.4154 0.2229 92.2099 2.2130 1.0655 203.2859 4.8789 2.3491 9.0915 0.2182 0.1051 NA NA NA NA cash
2019-06-20 TRUE PB INST NA NA 0.0918 35 0.1150 662.9 1190.00 TRUE 4.2300 2.9600 7.190 TRUE 3.890 TRUE 0.7220 TRUE 0.1940 TRUE 3.0000 TRUE 0.0117 TRUE 2.9883 NA NA NA NA NA NA NA NA NA NA NA NA 5.87 78.4 1083.9 30.2 cash
2019-06-20 TRUE PBR1 EOF PBR CCMT 0.0916 35 0.1158 691.4 751.00 TRUE 2.5300 4.0100 6.530 TRUE 4.640 TRUE 0.2400 TRUE 0.5740 TRUE 1.5500 TRUE 0.0043 TRUE 1.5457 26652.000 0.0216 0.0049 18.4280 0.1740 0.1237 40.6263 0.3837 0.2726 0.7755 0.0073 0.0052 NA NA NA NA cash
2019-06-20 TRUE PBR2 EOF PBR FBM 0.0904 35 0.0937 94.3 33.00 TRUE 0.1650 1.1900 1.350 TRUE 0.796 TRUE 0.1810 TRUE 0.1210 TRUE 0.0346 TRUE -0.0144 TRUE 0.0331 98956.000 0.0802 0.0403 9.3301 0.1336 0.0788 20.5692 0.2945 0.1737 0.8610 0.0123 0.0073 NA NA NA NA cash
2019-06-20 TRUE SCH1 EOF SCH CCMT 0.0948 35 0.1027 225.7 61.70 TRUE 8.3400 4.9900 13.300 TRUE 1.260 TRUE 2.1900 TRUE 0.2470 TRUE 9.2200 TRUE 0.1440 TRUE 9.0760 855180.000 0.6934 0.8016 193.0263 11.3739 1.0775 425.5459 25.0749 2.3755 40.9967 2.4157 0.2289 NA NA NA NA cash
2019-06-20 TRUE SCH2 EOF SCH FBM 0.0950 35 0.1014 182.9 41.10 TRUE 5.1000 1.6500 6.750 TRUE 1.280 TRUE 0.7050 TRUE 0.3000 TRUE 5.9400 TRUE 0.0689 TRUE 5.8711 518283.000 0.4202 0.5530 94.7717 3.4984 0.6634 208.9338 7.7126 1.4625 22.9094 0.8457 0.1604 NA NA NA NA cash
2019-06-20 TRUE SIM1 EOF SIM CCMT 0.0921 20 0.1226 1525.0 2040.00 TRUE 8.0300 1.0900 9.110 TRUE 4.360 TRUE 0.2000 TRUE 0.0653 TRUE 5.7400 TRUE -0.0026 TRUE 5.7150 84869.000 0.0688 0.0578 129.4252 0.7732 0.3700 285.3309 1.7045 0.8158 19.9672 0.1193 0.0571 NA NA NA NA cash
2019-06-24 TRUE ARR1 EOF ARR CCMT 0.0932 40 0.0989 142.5 156.00 TRUE 1.6500 6.6400 8.280 TRUE 0.837 TRUE 0.4570 TRUE 0.0718 TRUE 8.6800 TRUE 0.0301 TRUE 8.6499 2520102.000 2.0434 1.6853 359.1145 20.8664 2.1093 791.7039 46.0022 4.6502 54.4126 3.1617 0.3196 NA NA NA NA cash
2019-06-24 TRUE ARR2 EOF ARR FBM 0.0938 40 0.1030 230.0 243.00 TRUE 0.8640 6.6600 7.530 TRUE 1.170 TRUE 0.4060 TRUE 0.0939 TRUE 8.0700 TRUE 0.0064 TRUE 8.0636 1935014.000 1.5690 1.2163 445.0532 14.5707 2.2640 981.1643 32.1225 4.9911 63.3827 2.0751 0.3224 NA NA NA NA cash
2019-06-24 TRUE HB INST NA NA 0.0930 80 0.0960 37.5 30.10 TRUE 7.6800 1.2700 8.950 TRUE 0.890 TRUE 1.5900 TRUE 0.3110 TRUE 8.7900 TRUE 0.2090 TRUE 8.5810 NA NA NA NA NA NA NA NA NA NA NA NA 6.98 85.7 26.4 25.6 cash
2019-06-24 TRUE PB INST NA NA 0.0934 40 0.1131 492.5 766.00 TRUE 1.9100 1.1400 3.050 TRUE 3.210 TRUE 0.2920 TRUE 0.2420 TRUE 0.8970 TRUE -0.0042 TRUE 0.8955 NA NA NA NA NA NA NA NA NA NA NA NA 6.17 72.9 680.7 23.5 cash
2019-06-24 TRUE PBR1 EOF PBR CCMT 0.0914 80 0.0953 48.8 49.90 TRUE 0.2370 0.4480 0.685 TRUE 0.901 TRUE 0.0353 TRUE 0.2890 TRUE 0.1080 TRUE -0.0163 TRUE 0.1065 4212543.000 3.4157 0.7824 205.3615 2.8856 3.7955 452.7399 6.3616 8.3676 8.6417 0.1214 0.1597 NA NA NA NA cash
2019-06-24 TRUE PBR2 EOF PBR FBM 0.0929 80 0.1072 178.8 97.90 TRUE 0.0780 0.9690 1.050 TRUE 1.220 TRUE 0.0433 TRUE 0.1570 TRUE 0.2090 TRUE -0.0144 TRUE 0.2075 686809.000 0.5569 0.2797 122.7671 0.7211 0.8379 270.6524 1.5898 1.8472 11.3291 0.0665 0.0773 NA NA NA NA cash
2019-06-24 TRUE STU1 EOF STU CCMT 0.0925 40 0.1140 537.5 707.00 TRUE 0.7850 0.7360 1.520 TRUE 2.720 TRUE 0.1020 TRUE 0.2370 TRUE 0.1600 TRUE -0.0160 TRUE 0.1585 811922.000 0.6583 0.1082 436.4081 1.2341 2.2084 962.1052 2.7207 4.8687 13.1723 0.0373 0.0667 NA NA NA NA cash
2019-06-24 TRUE STU2 EOF STU FBM 0.0935 40 0.1039 260.0 231.00 TRUE 0.3290 0.5360 0.865 TRUE 1.450 TRUE 0.0285 TRUE 0.1190 TRUE 0.0277 TRUE -0.0232 TRUE 0.0262 145354.000 0.1179 0.0413 37.7920 0.1257 0.2108 83.3163 0.2772 0.4646 2.4333 0.0081 0.0136 NA NA NA NA cash
2019-06-25 TRUE CAR1 EOF CAR CCMT 0.0954 40 0.1011 142.5 107.00 TRUE 0.0110 2.5400 2.550 TRUE 1.330 TRUE 0.2330 TRUE 0.3520 TRUE 0.3080 TRUE -0.0082 TRUE 0.2830 455968.000 0.3697 0.1984 64.9754 1.1627 0.6064 143.2449 2.5633 1.3370 6.4063 0.1146 0.0598 NA NA NA NA cash
2019-06-25 TRUE CAR2 EOF CAR FBM 0.0934 40 0.1150 540.0 452.00 TRUE 0.4890 2.5700 3.060 TRUE 2.520 TRUE 0.0541 TRUE 0.1940 TRUE 0.3790 TRUE -0.0088 TRUE 0.3540 715361.000 0.5800 0.2975 386.2949 2.1890 1.8027 851.6258 4.8259 3.9743 36.3943 0.2062 0.1698 NA NA NA NA cash
2019-06-25 TRUE MUR1 EOF MUR CCMT 0.0954 20 0.1507 2765.0 3970.00 TRUE 4.0400 5.0100 9.060 TRUE 9.360 TRUE 0.0604 TRUE 0.2980 TRUE 0.3880 TRUE -0.0130 TRUE 0.3630 1980078.000 1.6055 1.0119 5474.9157 17.9395 18.5335 12069.9991 39.5494 40.8590 633.9285 2.0772 2.1460 NA NA NA NA cash
2019-06-25 TRUE MUR2 EOF MUR FBM 0.0950 20 0.1818 4340.0 5770.00 TRUE 4.5800 2.2400 6.830 TRUE 13.300 TRUE 0.0493 TRUE 0.2040 TRUE 0.5190 TRUE -0.0154 TRUE 0.4940 2388943.000 1.9371 1.4252 10368.0126 16.3165 31.7729 22857.3206 35.9713 70.0466 1417.0689 2.2301 4.3426 NA NA NA NA cash
2019-06-25 TRUE SCH1 EOF SCH CCMT 0.0918 20 0.2330 7060.0 8320.00 TRUE 26.1000 5.9100 32.000 TRUE 3.180 TRUE 0.7900 TRUE 0.1930 TRUE 19.1000 TRUE 0.1990 TRUE 18.9010 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-06-25 TRUE SCH2 EOF SCH FBM 0.0957 40 0.1090 332.5 181.00 TRUE 1.4400 11.5000 12.900 TRUE 2.000 TRUE 0.8270 TRUE 0.8160 TRUE 11.3000 TRUE 0.0467 TRUE 11.2750 601273.000 0.4875 0.6415 199.9233 7.7564 1.2025 440.7508 17.0998 2.6511 48.3279 1.8750 0.2907 NA NA NA NA cash
2019-06-25 TRUE SIM1 EOF SIM CCMT 0.0922 40 0.1196 685.0 854.00 TRUE 2.2000 0.7590 2.960 TRUE 2.150 TRUE 0.0755 TRUE 0.0809 TRUE 0.8120 TRUE -0.0086 TRUE 0.7870 1398409.000 1.1339 0.9522 957.9102 4.1393 3.0066 2111.8088 9.1255 6.6283 147.7823 0.6386 0.4638 NA NA NA NA cash
2019-06-25 TRUE SIM2 EOF SIM FBM 0.0913 40 0.1301 970.0 1390.00 TRUE 0.8520 2.0700 2.930 TRUE 2.050 TRUE 0.0771 TRUE 0.0354 TRUE 0.1260 TRUE -0.0174 TRUE 0.1010 3757183.000 3.0465 2.0783 3644.4675 11.0085 7.7022 8034.5931 24.2694 16.9803 456.7705 1.3797 0.9653 NA NA NA NA cash
2019-07-09 TRUE PBR1 EOF PBR CCMT 0.0911 50 0.0966 110.0 NA FALSE 0.1130 0.1600 0.273 TRUE 0.609 TRUE 0.0363 TRUE 0.0978 TRUE 0.0498 TRUE -0.0135 TRUE 0.0483 317765.000 0.2577 0.0590 34.9542 0.0867 0.1935 77.0599 0.1912 0.4266 1.4709 0.0037 0.0081 NA NA NA NA cash
2019-07-09 TRUE SCH1 EOF SCH CCMT 0.0917 50 0.1056 278.0 NA FALSE 1.8200 0.9610 2.780 TRUE 1.730 TRUE 0.2450 TRUE 0.2580 TRUE 1.5700 TRUE 0.0058 TRUE 1.5450 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-07-09 TRUE SCH2 EOF SCH FBM 0.0911 50 0.0941 60.0 NA FALSE 0.6540 0.3790 1.030 TRUE 1.150 TRUE 0.3850 TRUE 0.2400 TRUE 0.5350 TRUE -0.0038 TRUE 0.5100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-07-17 TRUE HB INST NA NA 0.0928 100 0.0941 13.0 30.50 TRUE 0.7340 0.6320 1.370 TRUE 0.728 TRUE 0.2100 TRUE 0.2500 TRUE 0.4080 TRUE -0.0014 TRUE 0.4065 NA NA NA NA NA NA NA NA NA NA NA NA 5.42 66.4 27.3 25.8 cash
2019-07-17 TRUE PB INST NA NA 0.0932 100 0.0969 37.0 69.60 TRUE 1.4400 1.1600 2.600 TRUE 0.821 TRUE 0.7140 TRUE 0.1490 TRUE 1.1700 TRUE 0.0552 TRUE 1.1148 NA NA NA NA NA NA NA NA NA NA NA NA 9.16 124.9 82.6 31.9 cash
2019-07-30 TRUE HB INST NA NA 0.0910 50 0.0915 10.0 11.20 TRUE 0.5790 0.2270 0.806 TRUE 0.555 TRUE 0.1000 TRUE 0.1620 TRUE 0.3380 TRUE -0.0059 TRUE 0.3365 NA NA NA NA NA NA NA NA NA NA NA NA 5.89 71.6 8.3 25.2 cash
2019-07-30 TRUE PB INST NA NA 0.0925 50 0.0977 104.0 156.00 TRUE 2.6900 0.2770 2.970 TRUE 1.000 TRUE 0.2220 TRUE 0.1770 TRUE 2.3200 TRUE 0.0538 TRUE 2.2662 NA NA NA NA NA NA NA NA NA NA NA NA 7.17 96.5 191.8 31.0 cash
2019-07-31 TRUE ARR1 EOF ARR CCMT 0.0896 50 0.1068 344.0 257.00 TRUE 0.9720 0.9430 1.920 TRUE 1.570 TRUE 0.0576 TRUE 0.2180 TRUE 0.2460 TRUE -0.0055 TRUE 0.2445 516741.000 0.4190 0.3456 177.7589 0.9921 0.8113 391.8873 2.1873 1.7886 26.9338 0.1503 0.1229 NA NA NA NA cash
2019-07-31 TRUE ARR2 EOF ARR FBM 0.0896 50 0.1291 790.0 727.00 TRUE 1.3300 1.4400 2.760 TRUE 2.950 TRUE 0.0421 TRUE 0.1590 TRUE 0.0723 TRUE -0.0050 TRUE 0.0708 466537.000 0.3783 0.2932 368.5642 1.2876 1.3763 812.5367 2.8387 3.0342 52.4895 0.1834 0.1960 NA NA NA NA cash
2019-07-31 TRUE PBR1 EOF PBR CCMT 0.0898 50 0.1309 822.0 363.00 TRUE 2.0600 2.0300 4.090 TRUE 3.700 TRUE 0.3330 TRUE 0.7410 TRUE 0.9350 TRUE -0.0037 TRUE 0.9335 35583.000 0.0289 0.0066 29.2492 0.1455 0.1317 64.4828 0.3208 0.2903 1.2308 0.0061 0.0055 NA NA NA NA cash
2019-07-31 TRUE PBR2 EOF PBR FBM 0.0925 50 0.1018 186.0 77.40 TRUE 0.8240 0.9480 1.770 TRUE 1.780 TRUE 0.0472 TRUE 0.3840 TRUE 0.2010 TRUE -0.0034 TRUE 0.1995 119581.000 0.0970 0.0487 22.2421 0.2117 0.2129 49.0349 0.4666 0.4693 2.0525 0.0195 0.0196 NA NA NA NA cash
2019-07-31 TRUE SCH2 EOF SCH FBM 0.0924 50 0.1008 168.0 60.40 TRUE 0.6920 0.5620 1.050 TRUE 1.480 TRUE 0.2420 TRUE 0.2840 TRUE 0.5040 TRUE 0.0122 TRUE 0.4790 2065022.000 1.6744 2.2032 346.9237 2.1683 3.0562 764.8280 4.7802 6.7378 83.8627 0.5241 0.7388 NA NA NA NA cash
2019-08-01 TRUE SIM1 EOF SIM CCMT 0.0906 80 0.1073 208.8 111.00 TRUE 0.1690 0.3950 0.565 TRUE 0.715 TRUE 0.0446 TRUE 0.0296 TRUE 0.1960 TRUE -0.0190 TRUE 0.1710 1210702.000 0.9817 0.8244 252.7340 0.6840 0.8657 557.1775 1.5080 1.9084 38.9907 0.1055 0.1335 NA NA NA NA cash
2019-08-01 TRUE SIM2 EOF SIM FBM 0.0931 100 0.0950 19.0 14.20 TRUE 0.0540 0.2970 0.351 TRUE 0.207 TRUE -0.0241 TRUE 0.0016 TRUE 0.2520 TRUE -0.0209 TRUE 0.2270 2119516.000 1.7186 1.1724 40.2708 0.7440 0.4387 88.7810 1.6401 0.9672 5.0472 0.0932 0.0550 NA NA NA NA cash
2019-08-06 TRUE MUR1 EOF MUR CCMT 0.0925 40 0.0992 167.5 90.90 TRUE 0.5950 0.5330 1.130 TRUE 1.020 TRUE -0.0486 TRUE 0.1050 TRUE 0.5250 TRUE -0.0221 TRUE 0.5000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-06 TRUE MUR2 EOF MUR FBM 0.0899 40 0.1594 1737.5 1570.00 TRUE 2.0900 1.8400 3.920 TRUE 5.440 TRUE -0.0543 TRUE 0.1450 TRUE 0.1970 TRUE -0.0220 TRUE 0.1720 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-06 TRUE SIM1 EOF SIM CCMT 0.0929 40 0.1064 337.5 361.00 TRUE 0.8880 0.9300 1.820 TRUE 1.350 TRUE 0.0102 TRUE 0.0239 TRUE 0.4920 TRUE -0.0175 TRUE 0.4670 724785.000 0.5877 0.4935 244.6149 1.3191 0.9785 539.2781 2.9081 2.1571 37.7381 0.2035 0.1510 NA NA NA NA cash
2019-08-06 TRUE SIM2 EOF SIM FBM 0.0919 40 0.1125 515.0 865.00 TRUE 0.9040 1.0700 1.980 TRUE 1.860 TRUE -0.0546 TRUE -0.0169 TRUE 0.2040 TRUE -0.0223 TRUE 0.1790 1208642.000 0.9800 0.6686 622.4506 2.3931 2.2481 1372.2547 5.2759 4.9561 78.0133 0.2999 0.2818 NA NA NA NA cash
2019-08-12 TRUE HB INST NA NA 0.0925 40 0.0955 75.0 113.00 TRUE 0.5420 0.6500 1.190 TRUE 1.220 TRUE 0.1790 TRUE 0.2850 TRUE 0.1090 TRUE -0.0220 TRUE 0.1075 NA NA NA NA NA NA NA NA NA NA NA NA 5.19 65.7 133.0 27.3 cash
2019-08-12 TRUE PB INST NA NA 0.0925 40 0.0945 50.0 92.90 TRUE 0.4660 0.4610 0.927 TRUE 1.030 TRUE 0.1020 TRUE 0.1910 TRUE 0.1940 TRUE -0.0240 TRUE 0.1925 NA NA NA NA NA NA NA NA NA NA NA NA 12.18 175.4 93.4 34.9 cash
2019-08-13 TRUE ARR1 EOF ARR CCMT 0.0922 40 0.1059 342.5 206.00 TRUE 1.3300 1.1300 2.450 TRUE 1.840 TRUE 0.1690 TRUE 0.1790 TRUE 0.5360 TRUE -0.0183 TRUE 0.5345 162409.000 0.1317 0.1086 55.6251 0.3979 0.2988 122.6311 0.8772 0.6588 8.4283 0.0603 0.0453 NA NA NA NA cash
2019-08-13 TRUE ARR2 EOF ARR FBM 0.0920 40 0.1460 1350.0 1030.00 TRUE 2.1200 2.0500 4.170 TRUE 4.650 TRUE 0.0834 TRUE 0.0833 TRUE 0.1740 TRUE -0.0169 TRUE 0.1725 266114.000 0.2158 0.1673 359.2539 1.1097 1.2374 792.0111 2.4464 2.7280 51.1635 0.1580 0.1762 NA NA NA NA cash
2019-08-13 TRUE PBR1 EOF PBR CCMT 0.0923 40 0.0951 70.0 41.60 TRUE 0.9130 0.5320 1.440 TRUE 1.540 TRUE 0.3280 TRUE 0.4640 TRUE 0.2370 TRUE -0.0177 TRUE 0.2355 108058.000 0.0876 0.0201 7.5641 0.1556 0.1664 16.6757 0.3430 0.3669 0.3183 0.0065 0.0070 NA NA NA NA cash
2019-08-13 TRUE SCH1 EOF SCH CCMT 0.0916 40 0.1055 347.5 372.00 TRUE 2.1000 1.2300 3.340 TRUE 3.080 TRUE 0.1920 TRUE 0.4730 TRUE 0.9780 TRUE -0.0158 TRUE 0.9530 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-13 TRUE SCH2 EOF SCH FBM 0.0909 40 0.1819 2275.0 1640.00 TRUE 3.5300 3.1300 6.660 TRUE 8.470 TRUE 0.1200 TRUE 0.5120 TRUE 1.0800 TRUE -0.0143 TRUE 1.0550 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-13 TRUE STU1 EOF STU CCMT 0.0935 40 0.0994 147.5 57.00 TRUE 0.4200 0.3910 0.810 TRUE 0.997 TRUE 0.3890 TRUE 0.0674 TRUE 0.3520 TRUE 0.0203 TRUE 0.3317 3789746.000 3.0729 0.5049 558.9875 3.0697 3.7784 1232.3439 6.7674 8.3298 16.8722 0.0927 0.1140 NA NA NA NA cash
2019-08-13 TRUE STU2 EOF STU FBM 0.0909 20 0.0992 415.0 319.00 TRUE 0.8120 1.0200 1.840 TRUE 3.120 TRUE 0.0507 TRUE 0.1460 TRUE 0.3590 TRUE -0.0201 TRUE 0.3575 57382.000 0.0465 0.0163 23.8135 0.1056 0.1790 52.4993 0.2328 0.3947 1.5333 0.0068 0.0115 NA NA NA NA cash
2019-08-16 TRUE PBR1 EOF PBR CCMT 0.0932 50 0.1029 194.0 70.80 TRUE 0.6710 0.6820 1.350 TRUE 1.800 TRUE 0.0721 TRUE 0.5460 TRUE 0.2390 TRUE -0.0193 TRUE 0.2375 568837.000 0.4612 0.1056 110.3544 0.7679 1.0239 243.2873 1.6930 2.2573 4.6438 0.0323 0.0431 NA NA NA NA cash
2019-08-16 TRUE PBR2 EOF PBR FBM 0.0936 50 0.0996 120.0 47.60 TRUE 0.7260 0.7190 1.450 TRUE 1.300 TRUE 0.0755 TRUE 0.3470 TRUE 0.3230 TRUE -0.0212 TRUE 0.3215 302378.000 0.2452 0.1232 36.2854 0.4384 0.3931 79.9947 0.9666 0.8666 3.3485 0.0405 0.0363 NA NA NA NA cash
2019-08-16 TRUE SIM1 EOF SIM CCMT 0.0921 50 0.1007 172.0 132.00 TRUE 0.5080 0.7620 1.270 TRUE 0.745 TRUE 0.0488 TRUE 0.0058 TRUE 0.2830 TRUE -0.0233 TRUE 0.2580 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-16 TRUE SIM2 EOF SIM FBM 0.0934 50 0.0945 22.0 9.23 TRUE 0.2110 0.2940 0.505 TRUE 0.200 TRUE -0.0075 TRUE -0.0418 TRUE 0.1280 TRUE -0.0209 TRUE 0.1030 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-20 TRUE MUR1 EOF MUR CCMT 0.0922 40 0.1032 275.0 144.00 TRUE 0.5110 0.5510 1.060 TRUE 1.620 TRUE 0.0190 TRUE 0.0751 TRUE 0.2810 TRUE -0.0043 TRUE 0.2560 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-20 TRUE MUR2 EOF MUR FBM 0.0914 40 0.1078 410.0 259.00 TRUE 0.8560 1.0500 1.910 TRUE 1.980 TRUE 0.0753 TRUE 0.1430 TRUE 0.4350 TRUE -0.0077 TRUE 0.4100 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-08-20 TRUE STU1 EOF STU CCMT 0.0906 40 0.0929 57.5 26.90 TRUE 0.2730 0.5200 0.793 TRUE 0.818 TRUE 0.2960 TRUE 0.0693 TRUE 0.2330 TRUE -0.0083 TRUE 0.2315 3240710.000 2.6277 0.4317 186.3408 2.5699 2.6509 410.8070 5.6656 5.8442 5.6244 0.0776 0.0800 NA NA NA NA cash
2019-08-20 TRUE STU2 EOF STU FBM 0.0911 40 0.1042 327.5 100.00 TRUE 0.4440 0.7660 1.210 TRUE 1.720 TRUE 0.3350 TRUE 0.1950 TRUE 0.2650 TRUE -0.0061 TRUE 0.2635 227441.000 0.1844 0.0646 74.4869 0.2752 0.3912 164.2139 0.6067 0.8624 4.7960 0.0177 0.0252 NA NA NA NA cash
2019-09-05 TRUE SCH2 EOF SCH FBM 0.0922 40 0.0995 182.5 92.80 TRUE 0.6320 0.5450 1.180 TRUE 1.500 TRUE 0.4280 TRUE 0.1560 TRUE 0.4190 FALSE -0.0001 TRUE 0.3940 269622.000 0.2186 0.2877 49.2060 0.3182 0.4044 108.4796 0.7014 0.8916 11.8947 0.0769 0.0978 NA NA NA NA cash
2019-10-17 TRUE MUR1 EOF MUR CCMT 0.0919 45 0.1202 628.9 1050.00 TRUE 5.8100 2.1600 7.970 TRUE 5.160 TRUE 0.2660 TRUE 2.3900 TRUE 7.6100 TRUE 0.0232 TRUE 7.5850 143361.000 0.1162 0.0733 90.1581 1.1426 0.7397 198.7626 2.5189 1.6308 10.4392 0.1323 0.0857 NA NA NA NA cash
2019-10-17 TRUE SIM1 EOF SIM CCMT 0.0933 45 0.0971 84.4 93.50 TRUE 2.4700 2.2200 4.690 TRUE 1.390 TRUE 0.0856 TRUE 0.2850 TRUE 1.4600 TRUE -0.0204 TRUE 1.4350 118567.000 0.0961 0.0807 10.0123 0.5561 0.1648 22.0732 1.2259 0.3633 1.5447 0.0858 0.0254 NA NA NA NA cash
2019-10-22 TRUE CAR1 EOF CAR CCMT 0.0918 30 0.1075 523.3 898.00 TRUE 1.5100 1.8200 3.330 TRUE 3.770 TRUE 0.0911 TRUE 0.6410 TRUE 0.5380 TRUE -0.0263 TRUE 0.5130 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cash
2019-10-22 TRUE HB INST NA NA 0.0916 40 0.0917 2.5 19.40 TRUE 4.8000 0.6980 5.500 TRUE 3.080 TRUE 0.0023 TRUE 0.9790 TRUE 3.7400 TRUE -0.0045 TRUE 3.7385 NA NA NA NA NA NA NA NA NA NA NA NA 6.77 66.3 18.5 14.6 cash
2019-10-22 TRUE MUR1 EOF MUR CCMT 0.0909 30 0.1177 893.3 1220.00 TRUE 5.4100 2.5700 7.990 TRUE 5.770 TRUE 0.1950 TRUE 0.0946 TRUE 4.4600 TRUE -0.0130 TRUE 4.4350 103374.000 0.0838 0.0528 92.3474 0.8260 0.5965 203.5892 1.8209 1.3150 10.6927 0.0956 0.0691 NA NA NA NA cash
2019-10-22 TRUE MUR2 EOF MUR FBM 0.0901 30 0.1006 350.0 812.00 TRUE 0.0080 9.4700 9.480 TRUE 3.910 TRUE 0.1490 TRUE 0.7200 TRUE 5.4700 TRUE 0.0335 TRUE 5.4450 13298.000 0.0108 0.0079 4.6543 0.1261 0.0520 10.2609 0.2779 0.1146 0.6361 0.0172 0.0071 NA NA NA NA cash
2019-10-22 TRUE SCH1 EOF SCH CCMT 0.0932 20 0.2170 6190.0 8370.00 TRUE 10.4000 6.0900 16.500 TRUE 20.300 TRUE 0.0202 TRUE 0.5260 TRUE 5.7000 TRUE -0.0240 TRUE 5.6750 4770.000 0.0039 0.0045 29.5263 0.0787 0.0968 65.0937 0.1735 0.2135 6.2711 0.0167 0.0206 NA NA NA NA cash
2019-10-22 TRUE SIM1 EOF SIM CCMT 0.0933 40 0.1002 172.5 272.00 TRUE 3.6400 1.4100 5.050 TRUE 1.490 TRUE 0.0308 TRUE 0.2140 TRUE 1.7900 TRUE -0.0211 TRUE 1.7650 122556.000 0.0994 0.0834 21.1409 0.6189 0.1826 46.6073 1.3644 0.4026 3.2615 0.0955 0.0282 NA NA NA NA cash
2019-10-22 TRUE SIM2 EOF SIM FBM 0.0922 40 0.0989 167.5 270.00 TRUE 3.2200 2.9200 6.130 TRUE 1.620 TRUE 0.0165 TRUE 0.2240 TRUE 2.8000 TRUE -0.0078 TRUE 2.7750 67806.000 0.0550 0.0375 11.3575 0.4157 0.1098 25.0388 0.9163 0.2422 1.4235 0.0521 0.0138 NA NA NA NA cash
2019-10-27 TRUE ARR1 EOF ARR CCMT 0.0942 40 0.1076 335.0 572.00 TRUE 2.2900 1.0000 3.290 TRUE 1.930 TRUE 0.1140 TRUE 0.1600 TRUE 1.5100 TRUE -0.0153 TRUE 1.5085 459964.000 0.3730 0.5709 154.0879 1.5133 0.8877 339.7023 3.3362 1.9571 43.3294 0.4255 0.2496 NA NA NA NA cash
2019-10-27 TRUE ARR2 EOF ARR FBM 0.0917 40 0.1169 630.0 949.00 TRUE 2.8600 1.2500 4.110 TRUE 2.410 TRUE -0.0755 TRUE 0.1330 TRUE 1.9400 TRUE -0.0079 TRUE 1.9385 370450.000 0.3004 0.5194 233.3835 1.5225 0.8928 514.5173 3.3566 1.9682 74.1379 0.4837 0.2836 NA NA NA NA cash
2019-10-27 TRUE HB INST NA NA 0.0931 40 0.0934 7.5 18.40 TRUE 0.7010 0.4780 1.180 TRUE 2.550 TRUE -0.0680 TRUE 1.3700 TRUE 0.0862 TRUE -0.0254 TRUE 0.0847 NA NA NA NA NA NA NA NA NA NA NA NA 6.44 62.8 23.0 14.6 cash
2019-10-27 TRUE PB INST NA NA 0.0922 40 0.0942 50.0 94.80 TRUE 1.4300 0.0428 1.860 TRUE 1.680 TRUE -0.0624 TRUE 0.6420 TRUE 1.0800 TRUE -0.0297 TRUE 1.0785 NA NA NA NA NA NA NA NA NA NA NA NA 5.71 57.1 111.6 15.5 cash
2019-10-27 TRUE PBR1 EOF PBR CCMT 0.0914 40 0.1137 557.5 747.00 TRUE 2.4700 1.5900 4.050 TRUE 3.610 TRUE 0.0606 TRUE 0.1810 TRUE 1.6200 TRUE -0.0105 TRUE 1.6185 55616.000 0.0451 0.0103 31.0059 0.2252 0.2008 68.3557 0.4966 0.4426 1.3047 0.0095 0.0084 NA NA NA NA cash
2019-10-27 TRUE STU1 EOF STU CCMT 0.0940 40 0.0954 35.0 39.90 TRUE 0.4160 0.5390 0.955 TRUE 2.970 TRUE 0.1330 TRUE 1.9500 TRUE 0.2580 TRUE -0.0234 TRUE 0.2565 1419295.000 1.1508 0.1891 49.6753 1.3554 4.2153 109.5142 2.9882 9.2931 1.4994 0.0409 0.1272 NA NA NA NA cash
2019-10-27 TRUE STU2 EOF STU FBM 0.0904 40 0.0953 122.5 178.00 TRUE 0.6000 0.0630 0.663 TRUE 3.140 TRUE 0.1620 TRUE 2.0700 TRUE 0.0839 TRUE -0.0178 TRUE 0.0824 1255560.000 1.0181 0.3568 153.8061 0.8324 3.9425 339.0809 1.8352 8.6915 9.9031 0.0536 0.2538 NA NA NA NA cash
2019-10-28 TRUE CAR1 EOF CAR CCMT 0.0927 40 0.1007 200.0 301.00 TRUE 0.9550 1.1300 2.090 TRUE 2.200 TRUE 0.0789 TRUE 0.5620 TRUE 0.2850 TRUE -0.0198 TRUE 0.2600 1016962.000 0.8246 0.4425 203.3924 2.1255 2.2373 448.3989 4.6858 4.9324 20.0536 0.2096 0.2206 NA NA NA NA cash
2019-10-28 TRUE CAR2 EOF CAR FBM 0.0932 40 0.1021 222.5 259.00 TRUE 3.5800 0.5610 4.140 TRUE 2.650 TRUE -0.0082 TRUE 1.0900 TRUE 2.5300 TRUE -0.0239 TRUE 2.5050 736085.000 0.5968 0.3061 163.7789 3.0474 1.9506 361.0670 6.7183 4.3003 15.4302 0.2871 0.1838 NA NA NA NA cash
2019-10-28 TRUE MUR1 EOF MUR CCMT 0.0911 40 0.1254 857.5 1320.00 TRUE 4.3700 1.4700 5.850 TRUE 4.950 TRUE 0.2420 TRUE 0.9020 TRUE 2.3800 TRUE -0.0170 TRUE 2.3550 3743409.000 3.0353 1.9130 3209.9732 21.8989 18.5299 7076.7070 48.2784 40.8510 371.6758 2.5356 2.1455 NA NA NA NA cash
2019-10-28 TRUE MUR2 EOF MUR FBM 0.0931 40 0.1768 2092.5 2450.00 TRUE 7.3400 2.6300 9.970 TRUE 7.280 TRUE 0.0776 TRUE 0.4190 TRUE 4.3200 TRUE -0.0074 TRUE 4.2950 2274123.000 1.8440 1.3567 4758.6024 22.6730 16.5556 10490.8148 49.9849 36.4985 650.3915 3.0989 2.2628 NA NA NA NA cash
2019-10-28 TRUE SCH1 EOF SCH CCMT 0.0949 40 0.1023 185.0 210.00 TRUE 6.6700 0.1790 6.850 TRUE 5.340 TRUE -0.1440 TRUE 2.5500 TRUE 4.7900 TRUE -0.0165 TRUE 4.7650 1543939.000 1.2519 1.4473 285.6287 10.5760 8.2446 629.6971 23.3158 18.1761 60.6645 2.2462 1.7511 NA NA NA NA cash
2019-10-28 TRUE SIM1 EOF SIM CCMT 0.0951 40 0.1052 252.5 341.00 TRUE 1.9800 1.0500 3.030 TRUE 1.430 TRUE 0.0905 TRUE 0.1500 TRUE 1.2500 TRUE -0.0242 TRUE 1.2250 1567831.000 1.2713 1.0675 395.8773 4.7505 2.2420 872.7512 10.4730 4.9427 61.0743 0.7329 0.3459 NA NA NA NA cash
2019-10-28 TRUE SIM2 EOF SIM FBM 0.0926 40 0.1000 185.0 228.00 TRUE 1.6000 0.8220 2.420 TRUE 1.040 TRUE 0.0545 TRUE 0.1570 TRUE 1.1100 TRUE -0.0214 TRUE 1.0850 2377650.000 1.9279 1.3152 439.8652 5.7539 2.4728 969.7269 12.6851 5.4514 55.1294 0.7212 0.3099 NA NA NA NA cash
2019-10-31 TRUE ARR1 EOF ARR CCMT 0.0940 50 0.1177 474.0 840.00 TRUE 1.4200 0.8810 2.300 TRUE 1.690 TRUE 0.0656 TRUE 0.0895 TRUE 0.7760 TRUE -0.0274 TRUE 0.7745 114859.000 0.0931 0.1425 54.4432 0.2642 0.1941 120.0254 0.5824 0.4279 15.3094 0.0743 0.0546 NA NA NA NA cash
2019-10-31 TRUE ARR2 EOF ARR FBM 0.0913 50 0.1093 360.0 637.00 TRUE 1.8600 0.5940 2.450 TRUE 1.470 TRUE 0.0580 TRUE 0.1190 TRUE 1.2000 TRUE -0.0254 TRUE 1.1985 39613.000 0.0321 0.0555 14.2607 0.0971 0.0582 31.4391 0.2140 0.1284 4.5301 0.0308 0.0185 NA NA NA NA cash
2019-10-31 TRUE HB INST NA NA 0.0918 100 0.0946 28.0 31.90 TRUE 0.7530 0.7100 1.460 TRUE 2.060 TRUE 0.0547 TRUE 0.9560 TRUE 0.1060 TRUE -0.0194 TRUE 0.1045 NA NA NA NA NA NA NA NA NA NA NA NA 10.08 86.1 36.5 8.8 cash
2019-10-31 TRUE MOS2 EOF MOS FBM 0.0919 50 0.1336 834.0 1210.00 TRUE 1.6300 1.3000 2.930 TRUE 3.160 TRUE 0.0486 TRUE 0.1880 TRUE 0.4560 TRUE -0.0087 TRUE 0.4545 97175.000 0.0788 0.0491 81.0440 0.2847 0.3071 178.6695 0.6277 0.6770 9.2767 0.0326 0.0351 NA NA NA NA cash
2019-10-31 TRUE PB INST NA NA 0.0909 100 0.1038 129.0 189.00 TRUE 0.9350 0.3710 1.310 TRUE 1.460 TRUE -0.0707 TRUE 0.6640 TRUE 0.4000 TRUE -0.0273 TRUE 0.3985 NA NA NA NA NA NA NA NA NA NA NA NA 8.11 72.9 199.1 11.0 cash
2019-10-31 TRUE PBR1 EOF PBR CCMT 0.0919 50 0.1289 740.0 928.00 TRUE 1.4600 1.0300 2.500 TRUE 3.680 TRUE 0.1960 TRUE 0.4090 TRUE 0.2090 TRUE -0.0187 TRUE 0.2075 23595.000 0.0191 0.0044 17.4603 0.0590 0.0868 38.4930 0.1300 0.1914 0.7347 0.0025 0.0037 NA NA NA NA cash
2019-11-12 TRUE HB INST NA NA 0.0903 100 0.0932 29.0 37.00 TRUE 0.7900 0.9640 1.750 TRUE 2.280 TRUE 0.1380 TRUE 1.0400 TRUE 0.1710 TRUE -0.0192 TRUE 0.1695 NA NA NA NA NA NA NA NA NA NA NA NA 12.75 89.8 49.1 1.7 cover
2019-11-12 TRUE MOS1 EOF MOS CCMT 0.0914 30 0.2035 3736.7 4880.00 TRUE 0.9400 5.8600 6.800 TRUE 12.200 TRUE 0.3270 TRUE 0.1650 TRUE 0.2990 TRUE -0.0245 TRUE 0.2975 14492.000 0.0118 0.0073 54.1518 0.0985 0.1768 119.3830 0.2173 0.3898 6.2082 0.0113 0.0203 NA NA NA NA cover
2019-11-12 TRUE MOS2 EOF MOS FBM 0.0918 30 0.1567 2163.3 2860.00 TRUE 3.0600 1.2600 4.310 TRUE 6.390 TRUE 0.0603 TRUE 0.2700 TRUE 0.5410 TRUE -0.0190 TRUE 0.5395 2419.000 0.0020 0.0012 5.2331 0.0104 0.0155 11.5369 0.0230 0.0341 0.5990 0.0012 0.0018 NA NA NA NA cover
2019-11-12 TRUE PB INST NA NA 0.0901 100 0.1082 181.0 280.00 TRUE 1.6500 0.9960 2.640 TRUE 2.260 TRUE 0.1900 TRUE 0.7970 TRUE 1.5700 TRUE -0.0110 TRUE 1.5685 NA NA NA NA NA NA NA NA NA NA NA NA 9.99 74.7 358.9 4.0 cover
2019-11-12 TRUE STU1 EOF STU CCMT 0.0929 30 0.1632 2343.3 4080.00 TRUE 7.6200 2.9400 10.600 TRUE 17.200 TRUE 0.6760 TRUE 2.2800 TRUE 2.0700 TRUE -0.0091 TRUE 2.0685 23080.000 0.0187 0.0031 54.0841 0.2446 0.3970 119.2339 0.5394 0.8752 1.6324 0.0074 0.0120 NA NA NA NA cover
2019-11-23 TRUE HB INST NA NA 0.0911 40 0.0914 7.5 34.00 TRUE 0.7360 0.7760 1.510 TRUE 1.390 TRUE 0.1670 TRUE 0.5330 TRUE 0.0859 TRUE -0.0123 TRUE 0.0844 NA NA NA NA NA NA NA NA NA NA NA NA 9.69 86.7 36.2 10.3 cover
2019-11-23 TRUE MOS2 EOF MOS FBM 0.0909 40 0.1413 1260.0 2020.00 TRUE 3.0400 0.5200 3.560 TRUE 5.590 TRUE -0.0272 TRUE 0.2200 TRUE 0.6090 TRUE -0.0153 TRUE 0.6075 8799.000 0.0071 0.0044 11.0867 0.0313 0.0492 24.4418 0.0691 0.1084 1.2690 0.0036 0.0056 NA NA NA NA cover
2019-11-23 TRUE MUR1 EOF MUR CCMT 0.0929 40 0.1319 975.0 9670.00 TRUE 6.6000 1.0700 7.670 TRUE 3.960 TRUE 0.2770 TRUE 0.5970 TRUE 3.2000 TRUE -0.0090 TRUE 3.1750 66846.000 0.0542 0.0342 65.1749 0.5127 0.2647 143.6845 1.1303 0.5836 7.5465 0.0594 0.0307 NA NA NA NA cover
2019-11-23 TRUE PB INST NA NA 0.0906 40 0.0996 225.0 359.00 TRUE 2.6000 0.7380 3.330 TRUE 2.150 TRUE 0.0920 TRUE 0.3740 TRUE 1.5000 TRUE -0.0260 TRUE 1.4985 NA NA NA NA NA NA NA NA NA NA NA NA 7.19 66.0 410.0 11.5 cover
2019-11-23 TRUE PBR1 EOF PBR CCMT 0.0918 40 0.1414 1240.0 1520.00 TRUE 2.1100 1.2600 3.370 TRUE 2.070 TRUE 0.0441 TRUE 0.4110 TRUE 0.1920 TRUE -0.0175 TRUE 0.1905 94456.000 0.0766 0.0175 117.1254 0.3183 0.1955 258.2147 0.7018 0.4311 4.9287 0.0134 0.0082 NA NA NA NA cover
2019-11-23 TRUE SCH1 EOF SCH CCMT 0.0925 40 0.0955 75.0 97.80 TRUE 1.5900 1.7400 3.330 TRUE 2.310 TRUE 0.2060 TRUE 1.5300 TRUE 0.3310 TRUE -0.0110 TRUE 0.3060 107710.000 0.0873 0.1010 8.0782 0.3587 0.2488 17.8093 0.7907 0.5485 1.7157 0.0762 0.0528 NA NA NA NA cover
2019-11-23 TRUE STU1 EOF STU CCMT 0.0909 40 0.2051 2855.0 4600.00 TRUE 7.0500 0.8160 7.860 TRUE 26.500 TRUE 0.3350 TRUE 7.0200 TRUE 1.4000 TRUE -0.0110 TRUE 1.3985 101063.000 0.0819 0.0135 288.5349 0.7944 2.6782 636.1040 1.7512 5.9043 8.7090 0.0240 0.0808 NA NA NA NA cover
2019-12-07 TRUE ARR1 EOF ARR CCMT 0.0918 40 0.1345 1067.5 1430.00 TRUE 2.0700 1.2800 3.340 TRUE 3.210 TRUE 0.2490 TRUE 0.0968 TRUE 0.2100 TRUE -0.0204 TRUE 0.2085 44375.000 0.0360 0.0551 47.3703 0.1482 0.1424 104.4326 0.3267 0.3140 13.3205 0.0417 0.0401 NA NA NA NA cover
2019-12-07 TRUE ARR2 EOF ARR FBM 0.0916 40 0.1702 1965.0 3450.00 TRUE 3.6100 0.8800 4.490 TRUE 7.080 TRUE 0.1100 TRUE 0.0494 TRUE 0.2130 TRUE -0.0182 TRUE 0.2115 166623.000 0.1351 0.2336 327.4142 0.7481 1.1797 721.8173 1.6493 2.6007 104.0083 0.2377 0.3747 NA NA NA NA cover
2019-12-07 TRUE HB INST NA NA 0.0901 40 0.0921 50.0 55.80 TRUE 0.6550 0.5480 1.200 TRUE 1.190 TRUE 0.2530 TRUE 0.3600 TRUE 0.1050 TRUE -0.0151 TRUE 0.1035 NA NA NA NA NA NA NA NA NA NA NA NA 10.14 88.4 71.3 9.7 cover
2019-12-07 TRUE MOS2 EOF MOS FBM 0.0898 40 0.1485 1467.5 1930.00 TRUE 3.6400 0.9440 4.590 TRUE 0.893 TRUE 0.0378 TRUE 0.2610 TRUE 0.8330 TRUE -0.0165 TRUE 0.8315 14494.000 0.0118 0.0073 21.2699 0.0665 0.0129 46.8917 0.1467 0.0285 2.4347 0.0076 0.0015 NA NA NA NA cover
2019-12-07 TRUE PB INST NA NA 0.0936 40 0.1033 242.5 494.00 TRUE 2.0900 0.5910 2.680 TRUE 2.010 TRUE 0.3310 TRUE 0.2560 TRUE 0.7610 TRUE -0.0133 TRUE 0.7595 NA NA NA NA NA NA NA NA NA NA NA NA 7.02 62.1 565.0 10.4 cover
2019-12-07 TRUE PBR1 EOF PBR CCMT 0.0904 40 0.1434 1325.0 1600.00 TRUE 2.4100 1.0300 3.440 TRUE 6.610 TRUE 0.2700 TRUE 0.5740 TRUE 0.3310 TRUE -0.0133 TRUE 0.3295 80485.000 0.0653 0.0149 106.6426 0.2769 0.5320 235.1043 0.6104 1.1729 4.4876 0.0117 0.0224 NA NA NA NA cover
2019-12-07 TRUE STU2 EOF STU FBM 0.0918 40 0.1752 2085.0 2190.00 TRUE 3.5800 0.2890 3.870 TRUE 7.080 TRUE 0.1400 TRUE 0.2360 TRUE 0.5930 TRUE -0.0138 TRUE 0.5915 85160.000 0.0691 0.0523 177.5586 0.3296 0.6029 391.4457 0.7266 1.3292 24.6969 0.0458 0.0839 NA NA NA NA cover
2019-12-11 TRUE HB INST NA NA 0.0921 100 0.0939 18.0 37.20 TRUE 0.7030 0.7450 1.450 TRUE 0.988 TRUE 0.0384 TRUE 0.2560 TRUE 0.0613 TRUE -0.0143 TRUE 0.0598 NA NA NA NA NA NA NA NA NA NA NA NA 12.51 95.5 46.8 4.7 cover
2019-12-11 TRUE MOS2 EOF MOS FBM 0.0953 40 0.1312 897.5 1520.00 TRUE 2.1600 0.8280 2.990 TRUE 3.370 TRUE -0.0040 TRUE 0.0502 TRUE 0.3280 TRUE -0.0204 TRUE 0.3265 139910.000 0.1134 0.0707 125.5692 0.4183 0.4715 276.8299 0.9223 1.0395 14.3733 0.0479 0.0540 NA NA NA NA cover
2019-12-11 TRUE PB INST NA NA 0.0889 100 0.1080 191.0 298.00 TRUE 1.3600 0.6960 2.060 TRUE 1.230 TRUE 0.0819 TRUE 0.1430 TRUE 0.5350 TRUE -0.0221 TRUE 0.5335 NA NA NA NA NA NA NA NA NA NA NA NA 11.72 89.3 324.5 4.7 cover
2019-12-11 TRUE PBR1 EOF PBR CCMT 0.0925 40 0.1156 577.5 979.00 TRUE 1.6500 1.3700 3.020 TRUE 3.770 TRUE 0.1470 TRUE 0.4950 TRUE 0.2880 TRUE -0.0245 TRUE 0.2865 530854.000 0.4304 0.0986 306.5682 1.6032 2.0013 675.8602 3.5344 4.4121 12.9006 0.0675 0.0842 NA NA NA NA cover
2019-12-11 TRUE PBR2 EOF PBR FBM 0.0912 40 0.1683 1927.5 1750.00 TRUE 3.0500 3.5600 6.610 TRUE 6.580 TRUE 1.0700 TRUE 0.2240 TRUE 0.9270 TRUE -0.0162 TRUE 0.9255 118241.000 0.0959 0.0482 227.9095 0.7816 0.7780 502.4493 1.7231 1.7152 21.0318 0.0721 0.0718 NA NA NA NA cover
2019-12-11 TRUE STU1 EOF STU CCMT 0.0939 40 0.1076 342.5 551.00 TRUE 0.9310 0.6210 1.550 TRUE 2.110 TRUE 0.0046 TRUE 0.1920 TRUE 0.0556 TRUE -0.0146 TRUE 0.0541 109543.000 0.0888 0.0356 37.5185 0.1698 0.2311 82.7132 0.3743 0.5096 2.7599 0.0125 0.0170 NA NA NA NA cover
2019-12-11 TRUE STU2 EOF STU FBM 0.0929 40 0.1159 575.0 821.00 TRUE 1.7900 0.5910 2.380 TRUE 2.450 TRUE 0.0024 TRUE 0.0754 TRUE 0.5370 TRUE -0.0158 TRUE 0.5355 11197.000 0.0091 0.0069 6.4383 0.0266 0.0274 14.1938 0.0588 0.0605 0.8955 0.0037 0.0038 NA NA NA NA cover
2019-12-13 TRUE MUR1 EOF MUR CCMT 0.0967 40 0.1108 352.5 531.00 TRUE 2.2900 0.9490 3.240 TRUE 3.560 TRUE 0.0946 TRUE 0.7640 TRUE 1.1500 TRUE -0.0150 TRUE 1.1250 777972.000 0.6308 0.3976 274.2351 2.5206 2.7696 604.5788 5.5570 6.1058 31.7531 0.2919 0.3207 NA NA NA NA cover
2019-12-13 TRUE MUR2 EOF MUR FBM 0.0912 20 0.1191 1395.0 2120.00 TRUE 3.2700 0.5590 3.830 TRUE 4.430 TRUE 0.0614 TRUE 0.0698 TRUE 0.3610 TRUE -0.0200 TRUE 0.3360 491969.000 0.3989 0.2935 686.2968 1.8842 2.1794 1513.0098 4.1540 4.8048 93.8010 0.2575 0.2979 NA NA NA NA cover
2019-12-13 TRUE SCH1 EOF SCH CCMT 0.0913 40 0.0980 167.5 197.00 TRUE 1.5700 1.9000 3.470 TRUE 3.350 TRUE 0.6270 TRUE 1.0900 TRUE 0.4880 TRUE 0.0019 TRUE 0.4630 82062.000 0.0665 0.0769 13.7454 0.2848 0.2749 30.3031 0.6278 0.6061 2.9194 0.0605 0.0584 NA NA NA NA cover
2019-12-13 TRUE SIM1 EOF SIM CCMT 0.0903 40 0.0999 240.0 369.00 TRUE 1.0300 0.8930 1.920 TRUE 1.200 TRUE 0.0554 TRUE 0.0363 TRUE 0.2630 TRUE -0.0151 TRUE 0.2380 323276.000 0.2621 0.2201 77.5862 0.6207 0.3879 171.0466 1.3684 0.8552 11.9697 0.0958 0.0598 NA NA NA NA cover
2019-12-17 TRUE ARR1 EOF ARR CCMT 0.0928 40 0.1426 1245.0 1920.00 TRUE 2.1400 0.9100 3.050 TRUE 4.930 TRUE 0.0767 TRUE 0.0480 TRUE 0.0961 TRUE -0.0107 TRUE 0.0946 266359.000 0.2160 0.3306 331.6170 0.8124 1.3131 731.0827 1.7910 2.8950 93.2503 0.2284 0.3693 NA NA NA NA cover
2019-12-17 TRUE ARR2 EOF ARR FBM 0.0946 40 0.1721 1937.5 3720.00 TRUE 3.7000 1.1200 4.820 TRUE 8.120 TRUE 0.0518 TRUE 0.0562 TRUE 0.1010 TRUE -0.0164 TRUE 0.0995 212853.000 0.1726 0.2984 412.4027 1.0260 1.7284 909.1830 2.2618 3.8104 131.0062 0.3259 0.5490 NA NA NA NA cover
2019-12-17 TRUE DCDC1 EOF DCDC CCMT 0.0911 50 0.1176 530.0 880.00 TRUE 1.2560 1.3400 2.610 TRUE 2.860 TRUE 0.0874 TRUE 0.3310 TRUE 0.1520 TRUE -0.0132 TRUE 0.1505 1400704.000 1.1357 0.6704 742.3731 3.6558 4.0060 1636.6358 8.0597 8.8317 80.5035 0.3964 0.4344 NA NA NA NA cover
2019-12-17 TRUE DCDC2 EOF DCDC FBM 0.0902 40 0.1224 805.0 1390.00 TRUE 1.8500 0.9060 2.760 TRUE 3.910 TRUE 0.0467 TRUE 0.1830 TRUE 0.1430 TRUE -0.0122 TRUE 0.1415 888963.000 0.7208 0.4173 715.6152 2.4535 3.4758 1577.6453 5.4091 7.6628 76.1045 0.2609 0.3697 NA NA NA NA cover
2019-12-17 TRUE HB INST NA NA 0.0923 100 0.0979 56.0 68.00 TRUE 0.7770 0.8310 1.610 TRUE 1.150 TRUE 0.1360 TRUE 0.2190 TRUE 0.0545 TRUE -0.0127 TRUE 0.0530 NA NA NA NA NA NA NA NA NA NA NA NA 11.80 93.4 86.6 5.7 cover
2019-12-17 TRUE MOS1 EOF MOS CCMT 0.0930 30 0.3471 8470.0 9730.00 TRUE 8.9400 4.4100 13.400 TRUE 19.200 TRUE 0.0864 TRUE 0.1020 TRUE 0.7060 TRUE -0.0151 TRUE 0.7045 293107.000 0.2377 0.1483 2482.6163 3.9276 5.6277 5473.1759 8.6589 12.4067 284.6165 0.4503 0.6452 NA NA NA NA cover
2019-12-17 TRUE MOS2 EOF MOS FBM 0.0915 30 0.1631 2386.7 3120.00 TRUE 3.7100 1.4000 5.110 TRUE 7.240 TRUE 0.1130 TRUE 0.1640 TRUE 0.4850 TRUE -0.0147 TRUE 0.4835 33324.000 0.0270 0.0168 79.5333 0.1703 0.2413 175.3391 0.3754 0.5319 9.1038 0.0195 0.0276 NA NA NA NA cover
2019-12-17 TRUE PB INST NA NA 0.0914 50 0.1194 560.0 968.00 TRUE 2.1600 0.5870 2.750 TRUE 3.030 TRUE 0.2480 TRUE 0.2330 TRUE 0.6640 TRUE -0.0117 TRUE 0.6625 NA NA NA NA NA NA NA NA NA NA NA NA 10.71 84.9 961.9 5.8 cover
2019-12-17 TRUE PBR1 EOF PBR CCMT 0.0920 40 0.1281 902.5 1110.00 TRUE 1.7000 1.2900 2.990 TRUE 6.130 TRUE 0.1330 TRUE 0.4990 TRUE 0.1280 TRUE -0.0146 TRUE 0.1265 490272.000 0.3975 0.0911 442.4705 1.4659 3.0054 975.4704 3.2318 6.6256 18.6194 0.0617 0.1265 NA NA NA NA cover
2019-12-17 TRUE PBR2 EOF PBR FBM 0.0894 40 0.2267 3432.5 2470.00 TRUE 3.2300 2.6100 5.850 TRUE 11.100 TRUE 0.5920 TRUE 0.3470 TRUE 0.4280 TRUE 0.0241 TRUE 0.4039 29123.000 0.0236 0.0119 99.9647 0.1704 0.3233 220.3822 0.3756 0.7127 9.2249 0.0157 0.0298 NA NA NA NA cover
2019-12-17 TRUE STU1 EOF STU CCMT 0.0910 40 0.1224 785.0 1030.00 TRUE 1.5800 0.0961 2.550 TRUE 3.650 TRUE 0.0589 TRUE 0.1210 TRUE 0.0428 TRUE -0.0136 TRUE 0.0413 249586.000 0.2024 0.0810 195.9250 0.6364 0.9110 431.9363 1.4031 2.0084 14.4123 0.0468 0.0670 NA NA NA NA cover
2019-12-17 TRUE STU2 EOF STU FBM 0.0919 40 0.1490 1427.5 1910.00 TRUE 3.0100 0.6840 3.690 TRUE 5.750 TRUE 0.0519 TRUE 0.1820 TRUE 0.4530 TRUE -0.0145 TRUE 0.4515 47062.000 0.0382 0.0289 67.1810 0.1737 0.2706 148.1072 0.3828 0.5966 9.3443 0.0242 0.0376 NA NA NA NA cover
2020-01-12 TRUE ARR1 EOF ARR CCMT 0.0911 40 0.1292 952.5 1540.00 TRUE 1.8800 0.8780 2.760 TRUE 4.070 TRUE 0.0875 TRUE 0.0634 TRUE 0.0613 TRUE -0.0192 TRUE 0.0598 682998.000 0.5538 0.8477 650.5556 1.8851 2.7798 1434.2149 4.1558 6.1284 182.9356 0.5301 0.7817 NA NA NA NA cover
2020-01-12 TRUE ARR2 EOF ARR FBM 0.0922 40 0.1758 2090.0 3430.00 TRUE 3.1700 0.8490 4.020 TRUE 7.090 TRUE 0.1840 TRUE 0.0760 TRUE 0.0862 TRUE -0.0283 TRUE 0.0847 212398.000 0.1722 0.2978 443.9118 0.8538 1.5059 978.6480 1.8824 3.3199 141.0156 0.2712 0.4784 NA NA NA NA cover
2020-01-12 TRUE DCDC1 EOF DCDC CCMT 0.0909 40 0.1098 472.5 742.00 TRUE 0.9010 0.9320 1.830 TRUE 3.170 TRUE 0.2280 TRUE 0.2580 TRUE 0.0993 TRUE -0.0234 TRUE 0.0978 2533613.000 2.0544 1.2126 1197.1321 4.6365 8.0316 2639.1975 10.2217 17.7064 129.8179 0.5028 0.8709 NA NA NA NA cover
2020-01-12 TRUE DCDC2 EOF DCDC FBM 0.0928 40 0.1132 510.0 823.00 TRUE 1.1100 0.7190 1.830 TRUE 3.170 TRUE 0.1460 TRUE 0.2090 TRUE 0.1190 TRUE -0.0245 TRUE 0.1175 2470440.000 2.0031 1.1596 1259.9244 4.5209 7.8313 2777.6293 9.9668 17.2649 133.9908 0.4808 0.8328 NA NA NA NA cover
2020-01-12 TRUE HB INST NA NA 0.0894 100 0.0921 27.0 61.30 TRUE 0.5810 0.5560 1.140 TRUE 1.130 TRUE 0.0228 TRUE 0.2100 TRUE 0.0716 TRUE -0.0204 TRUE 0.0701 NA NA NA NA NA NA NA NA NA NA NA NA 10.94 92.5 73.2 8.4 cover
2020-01-12 TRUE MOS2 EOF MOS FBM 0.0935 40 0.1580 1612.5 1820.00 TRUE 2.4000 0.7230 3.120 TRUE 5.780 TRUE 0.0854 TRUE 0.1250 TRUE 0.3360 TRUE -0.0050 TRUE 0.3345 51849.000 0.0420 0.0262 83.6065 0.1618 0.2997 184.3189 0.3566 0.6607 9.5700 0.0185 0.0343 NA NA NA NA cover
2020-01-12 TRUE PB INST NA NA 0.0919 50 0.1198 558.0 974.00 TRUE 1.7800 0.3260 2.110 TRUE 3.110 TRUE 0.8780 TRUE 0.1290 TRUE 0.4600 TRUE -0.0184 TRUE 0.4585 NA NA NA NA NA NA NA NA NA NA NA NA 9.58 83.9 914.0 9.9 cover
2020-01-12 TRUE PBR1 EOF PBR CCMT 0.0928 40 0.1215 717.5 766.00 TRUE 1.0100 0.7920 1.800 TRUE 3.730 TRUE 0.1280 TRUE 0.2250 TRUE 0.0948 TRUE -0.0246 TRUE 0.0933 288761.000 0.2341 0.0536 207.1860 0.5198 1.0771 456.7623 1.1459 2.3745 8.7185 0.0219 0.0453 NA NA NA NA cover
2020-01-12 TRUE STU1 EOF STU CCMT 0.0901 40 0.1126 562.5 880.00 TRUE 1.1700 0.2810 1.450 TRUE 3.040 TRUE 0.2770 TRUE 0.1040 TRUE 0.0638 TRUE -0.0264 TRUE 0.0623 828662.000 0.6719 0.2690 466.1224 1.2016 2.5191 1027.6134 2.6490 5.5537 34.2881 0.0884 0.1853 NA NA NA NA cover
2020-01-12 TRUE STU2 EOF STU FBM 0.0928 40 0.1355 1067.5 1570.00 TRUE 1.8100 0.5850 2.400 TRUE 5.190 TRUE 0.2020 TRUE 0.1430 TRUE 0.1200 TRUE -0.0124 TRUE 0.1185 453793.000 0.3680 0.2786 484.4240 1.0891 2.3552 1067.9612 2.4010 5.1922 67.3793 0.1515 0.3276 NA NA NA NA cover
2020-01-13 TRUE SCH1 EOF SCH CCMT 0.0915 40 0.1185 675.0 682.00 TRUE 1.2800 1.2900 2.570 TRUE 3.910 TRUE 0.1290 TRUE 0.4210 TRUE 0.1520 TRUE -0.0204 TRUE 0.1270 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-01-16 TRUE ARR1 EOF ARR CCMT 0.0926 40 0.1232 765.0 1300.00 TRUE 1.4200 0.5270 1.940 TRUE 2.780 TRUE 0.0644 TRUE 0.0426 TRUE 0.0764 TRUE -0.0243 TRUE 0.0749 1263704.000 1.0247 1.5684 966.7336 2.4516 3.5131 2131.2608 5.4048 7.7450 271.8445 0.6894 0.9879 NA NA NA NA cover
2020-01-16 TRUE ARR2 EOF ARR FBM 0.0903 40 0.1399 1240.0 1760.00 TRUE 1.3200 3.5600 4.880 TRUE 4.340 TRUE 0.0335 TRUE 0.0641 TRUE 0.0510 TRUE -0.0234 TRUE 0.0495 483358.000 0.3919 0.6777 599.3639 2.3588 2.0978 1321.3577 5.2002 4.6248 190.3974 0.7493 0.6664 NA NA NA NA cover
2020-01-16 TRUE DCDC1 EOF DCDC CCMT 0.0929 80 0.1164 293.8 458.00 TRUE 0.0750 1.6800 1.760 TRUE 1.760 TRUE 0.0387 TRUE 0.1830 TRUE 0.0723 TRUE -0.0247 TRUE 0.0708 1549805.000 1.2566 0.7417 455.2552 2.7277 2.7277 1003.6557 6.0134 6.0134 49.3682 0.2958 0.2958 NA NA NA NA cover
2020-01-16 TRUE DCDC2 EOF DCDC FBM 0.0913 40 0.1072 397.5 684.00 TRUE 0.8820 0.6400 1.520 TRUE 2.060 TRUE 0.1090 TRUE 0.1350 TRUE 0.0709 TRUE -0.0282 TRUE 0.0694 1522503.000 1.2345 0.7146 605.1949 2.3142 3.1364 1334.2128 5.1019 6.9144 64.3614 0.2461 0.3335 NA NA NA NA cover
2020-01-16 TRUE HB INST NA NA 0.0958 100 0.0992 34.0 82.70 TRUE 0.6780 0.1170 0.794 TRUE 1.330 TRUE 0.0949 TRUE 0.1620 TRUE 0.1090 TRUE -0.0218 TRUE 0.1075 NA NA NA NA NA NA NA NA NA NA NA NA 9.11 85.6 100.4 13.3 cover
2020-01-16 TRUE MOS2 EOF MOS FBM 0.0952 40 0.1447 1237.5 1880.00 TRUE 2.4300 0.6620 3.100 TRUE 6.110 TRUE 0.0452 TRUE 0.0863 TRUE 0.2410 TRUE -0.0242 TRUE 0.2395 118005.000 0.0957 0.0596 146.0312 0.3658 0.7210 321.9404 0.8065 1.5895 16.7155 0.0419 0.0825 NA NA NA NA cover
2020-01-16 TRUE PB INST NA NA 0.0958 40 0.1043 212.5 384.00 TRUE 1.0100 0.4490 1.460 TRUE 1.790 TRUE 0.1300 TRUE 0.1790 TRUE 0.1850 TRUE -0.0200 TRUE 0.1835 NA NA NA NA NA NA NA NA NA NA NA NA 7.00 68.6 564.9 15.2 cover
2020-01-16 TRUE PBR1 EOF PBR CCMT 0.0920 40 0.1158 595.0 920.00 TRUE 1.1500 1.1700 2.310 TRUE 2.820 TRUE 0.0704 TRUE 0.1710 TRUE 0.1230 TRUE -0.0236 TRUE 0.1215 1706806.000 1.3839 0.3170 1015.5496 3.9427 4.8132 2238.8806 8.6921 10.6112 42.7349 0.1659 0.2025 NA NA NA NA cover
2020-01-16 TRUE SCH1 EOF SCH CCMT 0.0904 40 0.1691 1967.5 2200.00 TRUE 2.7800 2.6100 5.400 TRUE 7.460 TRUE 0.0355 TRUE 0.2580 TRUE 0.1200 TRUE -0.0220 TRUE 0.0950 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-01-16 TRUE SCH2 EOF SCH FBM 0.0928 40 0.2181 3132.5 2580.00 TRUE 3.5900 2.3100 5.900 TRUE 9.580 TRUE -0.0593 TRUE 0.3070 TRUE 0.2550 TRUE -0.0218 TRUE 0.2300 749300.000 0.6076 0.7994 2347.1822 4.4209 7.1783 5174.5980 9.7463 15.8253 567.3901 1.0687 1.7352 NA NA NA NA cover
2020-01-16 TRUE STU1 EOF STU CCMT 0.0935 40 0.1191 640.0 869.00 TRUE 1.1700 0.6060 1.770 TRUE 2.380 TRUE 0.0200 TRUE 0.0754 TRUE 0.0622 TRUE -0.0233 TRUE 0.0607 1691925.000 1.3719 0.5493 1082.8320 2.9947 4.0268 2387.2114 6.6021 8.8774 79.6534 0.2203 0.2962 NA NA NA NA cover
2020-01-16 TRUE STU2 EOF STU FBM 0.0934 40 0.1269 837.5 1160.00 TRUE 1.7300 0.5690 2.300 TRUE 3.650 TRUE 0.0551 TRUE 0.0988 TRUE 0.1950 TRUE -0.0237 TRUE 0.1935 336275.000 0.2727 0.2064 281.6303 0.7734 1.2274 620.8822 1.7051 2.7059 39.1724 0.1076 0.1707 NA NA NA NA cover
2020-01-21 TRUE CAR1 EOF CAR CCMT 0.0940 40 0.0980 100.0 144.00 TRUE 0.7910 0.8820 1.670 TRUE 1.190 TRUE 0.0647 TRUE 0.0644 TRUE 0.0361 TRUE -0.0194 TRUE 0.0111 873896.000 0.7086 0.3803 87.3896 1.4594 1.0399 192.6591 3.2174 2.2926 8.6162 0.1439 0.1025 NA NA NA NA cover
2020-01-21 TRUE CAR2 EOF CAR FBM 0.0941 40 0.1091 375.0 526.00 TRUE 1.1600 1.2900 2.440 TRUE 2.260 TRUE 0.0187 TRUE 0.1170 TRUE 0.2290 TRUE -0.0226 TRUE 0.2040 359533.000 0.2915 0.1495 134.8249 0.8773 0.8125 297.2349 1.9340 1.7913 12.7023 0.0826 0.0766 NA NA NA NA cover
2020-01-21 TRUE MUR1 EOF MUR CCMT 0.0921 40 0.1081 400.0 593.00 TRUE 2.2800 1.2900 3.580 TRUE 3.560 TRUE 0.0932 TRUE 0.4460 TRUE 1.1000 TRUE -0.0219 TRUE 1.0750 145011.000 0.1176 0.0741 58.0044 0.5191 0.5162 127.8765 1.1445 1.1381 6.7162 0.0601 0.0598 NA NA NA NA cover
2020-01-21 TRUE MUR2 EOF MUR FBM 0.0939 40 0.1808 2172.5 3960.00 TRUE 4.4300 -0.4900 3.940 TRUE 8.740 TRUE 0.0509 TRUE 0.1240 TRUE 0.2550 TRUE -0.0242 TRUE 0.2300 192573.000 0.1561 0.1149 418.3648 0.7587 1.6831 922.3271 1.6727 3.7105 57.1809 0.1037 0.2300 NA NA NA NA cover
2020-01-21 TRUE SCH1 EOF SCH CCMT 0.0939 40 0.0980 102.5 191.00 TRUE 1.0100 0.9670 1.980 TRUE 2.470 TRUE 0.0685 TRUE 0.3930 TRUE 0.0642 TRUE -0.0181 TRUE 0.0392 48586.000 0.0394 0.0455 4.9801 0.0962 0.1200 10.9791 0.2121 0.2646 1.0577 0.0204 0.0255 NA NA NA NA cover
2020-01-21 TRUE SCH2 EOF SCH FBM 0.0940 40 0.1561 1552.5 1420.00 TRUE 2.7600 1.4500 4.210 TRUE 7.430 TRUE -0.0847 TRUE 0.3240 TRUE 0.3180 TRUE -0.0221 TRUE 0.2930 270637.000 0.2194 0.2887 420.1639 1.1394 2.0108 926.2934 2.5119 4.4331 101.5673 0.2754 0.4861 NA NA NA NA cover
2020-01-24 TRUE CAR1 EOF CAR CCMT 0.0917 40 0.0960 107.5 97.80 TRUE 0.6030 0.3530 0.955 TRUE 0.760 TRUE 0.1320 TRUE 0.0452 TRUE 0.1110 TRUE -0.0221 TRUE 0.0860 682002.000 0.5530 0.2968 73.3152 0.6513 0.5183 161.6307 1.4359 1.1427 7.2286 0.0642 0.0511 NA NA NA NA cover
2020-01-24 TRUE CAR2 EOF CAR FBM 0.0936 40 0.1015 197.5 317.00 TRUE 1.2000 0.2850 1.480 TRUE 1.890 TRUE 0.0330 TRUE 0.1330 TRUE 0.4170 TRUE -0.0190 TRUE 0.3920 823519.000 0.6677 0.3424 162.6450 1.2188 1.5565 358.5672 2.6870 3.4314 15.3234 0.1148 0.1466 NA NA NA NA cover
2020-01-24 TRUE MUR1 EOF MUR CCMT 0.0908 40 0.1080 430.0 565.00 TRUE 2.4100 0.5870 3.000 TRUE 3.730 TRUE 0.0518 TRUE 0.3890 TRUE 1.0800 TRUE -0.0208 TRUE 1.0550 1679941.000 1.3622 0.8585 722.3746 5.0398 6.2662 1592.5471 11.1108 13.8144 83.6422 0.5836 0.7255 NA NA NA NA cover
2020-01-24 TRUE MUR2 EOF MUR FBM 0.0930 40 0.1388 1145.0 1550.00 TRUE 3.5500 0.2590 3.290 TRUE 4.940 TRUE 0.0375 TRUE 0.1200 TRUE 1.0200 TRUE -0.0236 TRUE 0.9950 1115637.000 0.9046 0.6656 1277.4044 3.6704 5.5112 2816.1657 8.0919 12.1501 174.5918 0.5017 0.7533 NA NA NA NA cover
2020-01-24 TRUE SCH1 EOF SCH CCMT 0.0922 40 0.0963 102.5 129.00 TRUE 0.6480 0.4590 1.110 TRUE 2.090 TRUE 0.0224 TRUE 0.3030 TRUE 0.0461 TRUE -0.0197 TRUE 0.0211 645121.000 0.5231 0.6047 66.1249 0.7161 1.3483 145.7790 1.5787 2.9725 14.0442 0.1521 0.2864 NA NA NA NA cover
2020-01-24 TRUE SCH2 EOF SCH FBM 0.0939 40 0.1118 447.5 485.00 TRUE 1.1600 1.3200 2.480 TRUE 3.770 TRUE -0.0179 TRUE 0.5040 TRUE 0.2000 TRUE -0.0215 TRUE 0.1750 1211855.000 0.9826 1.2929 542.3051 3.0054 4.5687 1195.5659 6.6257 10.0721 131.0927 0.7265 1.1044 NA NA NA NA cover
2020-01-24 TRUE SIM1 EOF SIM CCMT 0.0929 40 0.1003 185.0 279.00 TRUE 0.7490 0.1420 0.892 TRUE 0.916 TRUE 0.0121 TRUE 0.0387 TRUE 0.1050 TRUE -0.0241 TRUE 0.0800 1009846.000 0.8188 0.6876 186.8215 0.9008 0.9250 411.8667 1.9859 2.0393 28.8220 0.1390 0.1427 NA NA NA NA cover
2020-01-24 TRUE SIM2 EOF SIM FBM 0.0928 40 0.1080 380.0 568.00 TRUE 1.7400 0.1730 1.910 TRUE 1.500 TRUE -0.0190 TRUE 0.0507 TRUE 0.8940 TRUE -0.0199 TRUE 0.8690 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-01-25 TRUE ARR1 EOF ARR CCMT 0.0899 40 0.1114 537.5 836.00 TRUE 1.2100 2.4400 3.640 TRUE 2.820 TRUE -0.0020 TRUE 0.0838 TRUE 0.0813 TRUE -0.0258 TRUE 0.0798 1047819.000 0.8496 1.3004 563.2027 3.8141 2.9548 1241.6367 8.4085 6.5143 158.3720 1.0725 0.8309 NA NA NA NA cover
2020-01-25 TRUE ARR2 EOF ARR FBM 0.0933 40 0.1326 982.5 1470.00 TRUE 1.8700 3.3200 5.190 TRUE 4.580 TRUE -0.0087 TRUE 0.0793 TRUE 0.1980 TRUE -0.0241 TRUE 0.1965 289880.000 0.2350 0.4064 284.8071 1.5045 1.3277 627.8857 3.3168 2.9269 90.4734 0.4779 0.4217 NA NA NA NA cover
2020-01-25 TRUE DCDC1 EOF DCDC CCMT 0.0948 40 0.1034 215.0 266.00 TRUE 0.5450 1.0300 1.580 TRUE 1.720 TRUE -0.0099 TRUE 0.1960 TRUE 0.0748 TRUE -0.0237 TRUE 0.0733 1771110.000 1.4361 0.8477 380.7887 2.7984 3.0463 839.4867 6.1693 6.7159 41.2930 0.3035 0.3303 NA NA NA NA cover
2020-01-25 TRUE DCDC2 EOF DCDC FBM 0.0918 40 0.1047 322.5 453.00 TRUE 0.9020 0.6670 1.570 TRUE 2.110 TRUE -0.0210 TRUE 0.1230 TRUE 0.1690 TRUE -0.0210 TRUE 0.1675 2008008.000 1.6282 0.9425 647.5826 3.1526 4.2369 1427.6606 6.9502 9.3407 68.8693 0.3353 0.4506 NA NA NA NA cover
2020-01-25 TRUE MOS2 EOF MOS FBM 0.0942 40 0.1286 860.0 1140.00 TRUE 1.9500 0.0320 1.980 TRUE 3.940 TRUE 0.0236 TRUE 0.0741 TRUE 0.4650 TRUE -0.0215 TRUE 0.4635 152424.000 0.1236 0.0770 131.0846 0.3018 0.6006 288.9892 0.6653 1.3240 15.0046 0.0345 0.0687 NA NA NA NA cover
2020-01-25 TRUE PBR1 EOF PBR CCMT 0.0936 40 0.1141 512.5 665.00 TRUE 0.9020 1.5700 2.470 TRUE 3.370 TRUE 0.0277 TRUE 0.1200 TRUE 0.1190 TRUE -0.0239 TRUE 0.1175 397629.000 0.3224 0.0738 203.7849 0.9821 1.3400 449.2641 2.1652 2.9542 8.5754 0.0413 0.0564 NA NA NA NA cover
2020-01-25 TRUE PBR2 EOF PBR FBM 0.0930 40 0.1429 1247.5 1200.00 TRUE 2.8300 1.6400 4.460 TRUE 6.470 TRUE 0.0919 TRUE 0.2500 TRUE 0.9550 TRUE -0.0216 TRUE 0.9535 48859.000 0.0396 0.0199 60.9516 0.2179 0.3161 134.3739 0.4804 0.6969 5.6247 0.0201 0.0292 NA NA NA NA cover
2020-01-25 TRUE STU1 EOF STU CCMT 0.0935 40 0.1173 595.0 818.00 TRUE 1.4300 0.6220 2.050 TRUE 3.310 TRUE 0.0335 TRUE 0.0711 TRUE 0.0468 TRUE -0.0214 TRUE 0.0453 1014040.000 0.8222 0.3292 603.3538 2.0788 3.3565 1330.1538 4.5829 7.3997 44.3828 0.1529 0.2469 NA NA NA NA cover
2020-01-25 TRUE STU2 EOF STU FBM 0.0937 40 0.1380 1107.5 1460.00 TRUE 2.1400 2.9300 5.060 TRUE 4.940 TRUE -0.0168 TRUE 0.1290 TRUE 0.2150 TRUE -0.0269 TRUE 0.2135 754536.000 0.6118 0.4632 835.6486 3.8180 3.7274 1842.2709 8.4171 8.2174 116.2316 0.5310 0.5185 NA NA NA NA cover
2020-02-06 TRUE ARR1 EOF ARR CCMT 0.0920 40 0.1417 1242.5 1410.00 TRUE 2.0100 1.5700 3.580 TRUE 4.360 TRUE 0.2040 TRUE 0.0251 TRUE 0.1830 TRUE -0.0083 TRUE 0.1815 125550.000 0.1018 0.1558 155.9959 0.4495 0.5474 343.9085 0.9909 1.2068 43.8659 0.1264 0.1539 NA NA NA NA cover
2020-02-06 TRUE ARR2 EOF ARR FBM 0.0948 40 0.1384 1090.0 1640.00 TRUE 1.9200 1.1000 3.020 TRUE 4.440 TRUE 0.1120 TRUE 0.0321 TRUE 0.0557 TRUE -0.0177 TRUE 0.0542 77301.000 0.0627 0.1084 84.2581 0.2334 0.3432 185.7554 0.5147 0.7567 26.7659 0.0742 0.1090 NA NA NA NA cover
2020-02-06 TRUE DCDC1 EOF DCDC CCMT 0.0932 40 0.0982 125.0 155.00 TRUE 0.5250 0.7280 1.250 TRUE 0.985 TRUE 0.0476 TRUE 0.0658 TRUE 0.0545 TRUE -0.0246 TRUE 0.0530 46180.000 0.0374 0.0221 5.7725 0.0577 0.0455 12.7261 0.1273 0.1003 0.6260 0.0063 0.0049 NA NA NA NA cover
2020-02-06 TRUE DCDC2 EOF DCDC FBM 0.0950 40 0.1454 1260.0 1220.00 TRUE 1.7500 1.3500 3.110 TRUE 4.310 TRUE 0.0181 TRUE 0.0249 TRUE 0.0786 TRUE -0.0236 TRUE 0.0771 111167.000 0.0901 0.0522 140.0704 0.3457 0.4791 308.7992 0.7622 1.0563 14.8962 0.0368 0.0510 NA NA NA NA cover
2020-02-06 TRUE HB INST NA NA 0.0937 40 0.0960 57.5 96.50 TRUE 0.5590 0.5800 1.140 TRUE 0.830 TRUE 0.0075 TRUE 0.0926 TRUE 0.0863 TRUE -0.0234 TRUE 0.0848 NA NA NA NA NA NA NA NA NA NA NA NA 11.44 97.5 118.1 7.8 cover
2020-02-06 TRUE MOS1 EOF MOS CCMT 0.0917 40 0.1409 1230.0 1470.00 TRUE 2.3900 1.3500 3.740 TRUE 6.150 TRUE -0.0001 TRUE 0.0673 TRUE 0.4660 TRUE -0.0312 TRUE 0.4645 115767.000 0.0939 0.0586 142.3934 0.4330 0.7120 313.9205 0.9545 1.5696 16.3245 0.0496 0.0816 NA NA NA NA cover
2020-02-06 TRUE MOS2 EOF MOS FBM 0.0944 40 0.1596 1630.0 1980.00 TRUE 2.8400 0.7760 3.620 TRUE 5.990 TRUE 0.0096 TRUE 0.0247 TRUE 0.3240 TRUE -0.0286 TRUE 0.3225 72173.000 0.0585 0.0365 117.6420 0.2613 0.4323 259.3535 0.5760 0.9531 13.4659 0.0299 0.0495 NA NA NA NA cover
2020-02-06 TRUE PB INST NA NA 0.0920 40 0.1014 235.0 383.00 TRUE 0.9270 0.8330 1.760 TRUE 1.630 TRUE 0.0419 TRUE 0.1090 TRUE 0.2820 TRUE -0.0279 TRUE 0.2805 NA NA NA NA NA NA NA NA NA NA NA NA 9.99 84.4 391.2 7.6 cover
2020-02-06 TRUE PBR1 EOF PBR CCMT 0.0930 40 0.1258 820.0 1170.00 TRUE 1.5100 0.8820 2.400 TRUE 4.230 TRUE 0.0603 TRUE 0.1030 TRUE 0.1430 TRUE -0.0184 TRUE 0.1415 1352996.000 1.0971 0.2513 1109.4567 3.2472 5.7232 2445.9083 7.1588 12.6173 46.6865 0.1366 0.2408 NA NA NA NA cover
2020-02-06 TRUE PBR2 EOF PBR FBM 0.0925 40 0.1186 652.5 981.00 TRUE 1.2400 1.4000 2.640 TRUE 3.810 TRUE 0.0027 TRUE 0.0777 TRUE 0.1440 TRUE -0.0161 TRUE 0.1425 120774.000 0.0979 0.0492 78.8050 0.3188 0.4601 173.7336 0.7029 1.0144 7.2722 0.0294 0.0425 NA NA NA NA cover
2020-02-06 TRUE STU1 EOF STU CCMT 0.0931 40 0.1125 485.0 947.00 TRUE 1.1600 0.1170 1.280 TRUE 2.230 TRUE 0.0002 TRUE 0.0380 TRUE 0.0500 TRUE -0.0182 TRUE 0.0485 799392.000 0.6482 0.2595 387.7051 1.0232 1.7826 854.7347 2.2558 3.9300 28.5197 0.0753 0.1311 NA NA NA NA cover
2020-02-06 TRUE STU2 EOF STU FBM 0.0919 40 0.1335 1040.0 1300.00 TRUE 2.1700 0.6320 2.800 TRUE 4.120 TRUE 0.0374 TRUE 0.0850 TRUE 0.2760 TRUE -0.0224 TRUE 0.2745 260040.000 0.2109 0.1596 270.4416 0.7281 1.0714 596.2156 1.6052 2.3619 37.6161 0.1013 0.1490 NA NA NA NA cover
2020-02-08 TRUE CAR1 EOF CAR CCMT 0.0934 30 0.0970 120.0 54.00 TRUE 0.5970 1.4400 2.040 TRUE 0.808 TRUE 0.0297 TRUE 0.0495 FALSE 0.0352 TRUE -0.0180 TRUE 0.0102 425545.000 0.3450 0.1852 51.0654 0.8681 0.3438 112.5788 1.9138 0.7580 5.0348 0.0856 0.0339 NA NA NA NA cover
2020-02-08 TRUE CAR2 EOF CAR FBM 0.0939 30 0.1002 210.0 251.00 TRUE 1.5200 0.6370 2.160 TRUE 1.370 TRUE 0.0182 TRUE 0.0483 FALSE 0.6660 TRUE -0.0232 TRUE 0.6410 649372.000 0.5265 0.2700 136.3681 1.4026 0.8896 300.6372 3.0923 1.9613 12.8477 0.1321 0.0838 NA NA NA NA cover
2020-02-08 TRUE MUR1 EOF MUR CCMT 0.0928 30 0.1550 2073.3 2530.00 TRUE 3.7700 0.1550 3.930 TRUE 9.830 TRUE 0.0427 TRUE 0.1100 FALSE 0.3750 TRUE -0.0221 TRUE 0.3500 1942390.000 1.5750 0.9926 4027.2219 7.6336 19.0937 8878.4135 16.8290 42.0940 466.3032 0.8839 2.2108 NA NA NA NA cover
2020-02-08 TRUE MUR2 EOF MUR FBM 0.0934 30 0.1535 2003.3 3180.00 TRUE 3.7700 3.3100 7.070 TRUE 8.830 TRUE 0.0192 TRUE 0.0750 FALSE 0.2620 TRUE -0.0156 TRUE 0.2370 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-02-08 TRUE SCH1 EOF SCH CCMT 0.0914 30 0.1085 570.0 530.00 TRUE 1.2400 1.0500 2.290 TRUE 3.400 TRUE 0.0102 TRUE 0.1830 FALSE 0.0417 TRUE -0.0179 TRUE 0.0167 620733.000 0.5033 0.5819 353.8178 1.4215 2.1105 780.0267 3.1338 4.6528 75.1471 0.3019 0.4482 NA NA NA NA cover
2020-02-08 TRUE SCH2 EOF SCH FBM 0.0924 30 0.2076 3840.0 2360.00 TRUE 3.4700 3.4200 6.890 TRUE 13.200 TRUE 0.0450 TRUE 0.2750 FALSE 0.1300 TRUE -0.0144 TRUE 0.1050 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-02-08 TRUE SIM1 EOF SIM CCMT 0.0933 30 0.1077 480.0 822.00 TRUE 1.0200 0.4300 1.450 TRUE 1.950 TRUE 0.1510 TRUE 0.0174 FALSE 0.0659 TRUE -0.0199 TRUE 0.0409 851901.000 0.6908 0.5801 408.9125 1.2353 1.6612 901.4885 2.7232 3.6623 63.0853 0.1906 0.2563 NA NA NA NA cover
2020-02-08 TRUE SIM2 EOF SIM FBM 0.0953 30 0.1183 766.7 913.00 TRUE 1.3400 0.4610 1.800 TRUE 2.540 TRUE 0.0009 TRUE 0.0056 FALSE 0.2030 TRUE -0.0243 TRUE 0.1780 1194057.000 0.9682 0.6605 915.4437 2.1493 3.0329 2018.1872 4.7384 6.6863 114.7349 0.2694 0.3801 NA NA NA NA cover
2020-02-19 TRUE DCDC1 EOF DCDC CCMT 0.0939 40 0.1450 1277.5 2030.00 TRUE 2.4100 3.1300 5.540 TRUE 5.700 TRUE 0.0930 TRUE 0.1670 FALSE 0.1350 TRUE -0.0176 TRUE 0.1335 678096.000 0.5498 0.3245 866.2676 3.7567 3.8651 1909.7736 8.2819 8.5211 93.9387 0.4074 0.4191 NA NA NA NA cover
2020-02-19 TRUE DCDC2 EOF DCDC FBM 0.0936 40 0.1940 2510.0 4200.00 TRUE 3.9800 4.9500 8.930 TRUE 10.000 TRUE 0.0551 TRUE 0.0642 FALSE 0.2470 TRUE -0.0191 TRUE 0.2455 254701.000 0.2065 0.1195 639.2995 2.2745 2.5470 1409.3997 5.0143 5.6151 67.9884 0.2419 0.2709 NA NA NA NA cover
2020-02-19 TRUE HB INST NA NA 0.0936 80 0.0990 67.5 96.10 TRUE 0.7180 0.8450 1.560 TRUE 1.070 TRUE 0.1010 TRUE 0.1120 FALSE 0.0545 TRUE -0.0167 TRUE 0.0530 NA NA NA NA NA NA NA NA NA NA NA NA 11.73 99.4 135.0 8.6 cover
2020-02-19 TRUE PB INST NA NA 0.0932 80 0.1020 110.0 188.00 TRUE 0.8070 1.2200 2.030 TRUE 1.410 TRUE 0.2430 TRUE 0.0790 FALSE 0.2660 TRUE -0.0139 TRUE 0.2645 NA NA NA NA NA NA NA NA NA NA NA NA 9.65 82.2 268.6 8.9 cover
2020-02-19 TRUE PBR1 EOF PBR CCMT 0.0933 40 0.1260 817.5 957.00 TRUE 1.5900 1.4000 3.000 TRUE 3.070 TRUE 0.0344 TRUE 0.0876 FALSE 0.2600 TRUE -0.0205 TRUE 0.2585 318964.000 0.2586 0.0592 260.7531 0.9569 0.9792 574.8562 2.1096 2.1588 10.9726 0.0403 0.0412 NA NA NA NA cover
2020-02-19 TRUE PBR2 EOF PBR FBM 0.0963 40 0.1780 2042.5 2740.00 TRUE 2.4700 3.5100 5.970 TRUE 5.230 TRUE 0.0639 TRUE 0.0819 FALSE 0.0387 TRUE -0.0238 TRUE 0.0372 24577.000 0.0199 0.0100 50.1985 0.1467 0.1285 110.6677 0.3235 0.2834 4.6324 0.0135 0.0119 NA NA NA NA cover
2020-02-21 TRUE ARR1 EOF ARR CCMT 0.0932 40 0.1151 547.5 978.00 TRUE 1.1200 0.6860 1.810 TRUE 2.250 TRUE -0.0021 TRUE 0.0284 TRUE 0.0256 TRUE -0.0111 TRUE 0.0241 289053.000 0.2344 0.3587 158.2565 0.5232 0.6504 348.8923 1.1534 1.4338 44.5016 0.1471 0.1829 NA NA NA NA cover
2020-02-21 TRUE DCDC1 EOF DCDC CCMT 0.0924 40 0.1027 257.5 364.00 TRUE 0.6780 0.6670 1.340 TRUE 1.760 TRUE 0.0001 TRUE 0.1590 TRUE 0.0887 TRUE -0.0301 TRUE 0.0872 1433729.000 1.1625 0.6862 369.1852 1.9212 2.5234 813.9057 4.2355 5.5630 40.0347 0.2083 0.2736 NA NA NA NA cover
2020-02-21 TRUE DCDC2 EOF DCDC FBM 0.0932 40 0.1107 437.5 689.00 TRUE 1.0600 0.6860 1.740 TRUE 2.240 TRUE 0.0130 TRUE 0.1050 TRUE 0.1360 TRUE -0.0239 TRUE 0.1345 1439878.000 1.1675 0.6758 629.9466 2.5054 3.2253 1388.7803 5.5234 7.1106 66.9937 0.2664 0.3430 NA NA NA NA cover
2020-02-21 TRUE HB INST NA NA 0.0935 80 0.0968 41.3 59.50 TRUE 0.5600 0.5000 1.060 TRUE 0.703 TRUE 0.0483 TRUE 0.0860 TRUE 0.0661 TRUE -0.0287 TRUE 0.0646 NA NA NA NA NA NA NA NA NA NA NA NA 13.38 93.5 67.7 1.6 cover
2020-02-21 TRUE MOS1 EOF MOS CCMT 0.0918 40 0.1187 672.5 868.00 TRUE 1.5300 1.0200 2.550 TRUE 3.680 TRUE 0.0163 TRUE 0.0963 TRUE 0.2160 TRUE -0.0226 TRUE 0.2145 830067.000 0.6731 0.4200 558.2201 2.1167 3.0546 1230.6519 4.6664 6.7343 63.9965 0.2427 0.3502 NA NA NA NA cover
2020-02-21 TRUE MOS2 EOF MOS FBM 0.0931 40 0.1410 1197.5 1610.00 TRUE 2.3000 1.0900 3.390 TRUE 4.820 TRUE 0.0215 TRUE 0.0448 TRUE 0.2760 TRUE -0.0243 TRUE 0.2745 223941.000 0.1816 0.1131 268.1693 0.7592 1.0794 591.2061 1.6736 2.3796 30.6961 0.0869 0.1236 NA NA NA NA cover
2020-02-21 TRUE PB INST NA NA 0.0932 80 0.1121 236.3 469.00 TRUE 0.9730 0.4570 1.430 TRUE 1.610 TRUE 0.0316 TRUE 0.0518 TRUE 0.2300 TRUE -0.0110 TRUE 0.2285 NA NA NA NA NA NA NA NA NA NA NA NA 13.03 99.4 540.5 4.9 cover
2020-02-21 TRUE PBR1 EOF PBR CCMT 0.0928 40 0.1112 460.0 674.00 TRUE 0.0941 0.9470 1.890 TRUE 1.640 TRUE -0.0073 TRUE 0.0936 TRUE 0.1220 TRUE -0.0167 TRUE 0.1205 1200944.000 0.9738 0.2230 552.4342 2.2698 1.9695 1217.8965 5.0040 4.3421 23.2467 0.0955 0.0829 NA NA NA NA cover
2020-02-21 TRUE PBR2 EOF PBR FBM 0.0917 40 0.1145 570.0 859.00 TRUE 1.2000 1.2700 2.470 TRUE 3.230 TRUE 0.0141 TRUE 0.0744 TRUE 0.2530 TRUE -0.0102 TRUE 0.2515 356971.000 0.2894 0.1454 203.4735 0.8817 1.1530 448.5776 1.9438 2.5419 18.7768 0.0814 0.1064 NA NA NA NA cover
2020-02-27 TRUE CAR1 EOF CAR CCMT 0.0938 40 0.0960 55.0 88.90 TRUE 0.7070 2.0000 2.710 TRUE 0.903 TRUE -0.0011 TRUE 0.0895 TRUE 0.0561 FALSE -0.0325 TRUE 0.0311 147489.000 0.1196 0.0642 8.1119 0.3997 0.1332 17.8835 0.8812 0.2936 0.7998 0.0394 0.0131 NA NA NA NA cover
2020-02-27 TRUE MUR1 EOF MUR CCMT 0.0948 40 0.1274 815.0 1050.00 TRUE 2.0700 1.1300 3.200 TRUE 4.380 TRUE -0.0091 TRUE 0.1070 TRUE 0.2270 FALSE -0.0329 TRUE 0.2020 407098.000 0.3301 0.2080 331.7849 1.3027 1.7831 731.4529 2.8720 3.9310 38.4166 0.1508 0.2065 NA NA NA NA cover
2020-02-27 TRUE MUR2 EOF MUR FBM 0.0951 40 0.2093 2855.0 4680.00 TRUE 5.2700 0.3370 5.610 TRUE 8.930 TRUE -0.0240 TRUE 0.0392 TRUE 0.1680 FALSE -0.0328 TRUE 0.1430 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-02-27 TRUE SCH1 EOF SCH CCMT 0.0921 40 0.1006 212.5 380.00 TRUE 1.0200 1.6700 2.690 TRUE 1.870 TRUE -0.0088 TRUE 0.1130 TRUE 0.0231 FALSE -0.0310 TRUE -0.0019 125732.000 0.1019 0.1179 26.7181 0.3382 0.2351 58.9026 0.7456 0.5183 5.6746 0.0718 0.0499 NA NA NA NA cover
2020-02-27 TRUE SCH2 EOF SCH FBM 0.0947 40 0.1295 870.0 857.00 TRUE 1.7800 2.1600 3.940 TRUE 4.400 TRUE -0.0196 TRUE 0.1690 TRUE 0.0652 FALSE -0.0315 TRUE 0.0402 316800.000 0.2569 0.3380 275.6160 1.2482 1.3939 607.6230 2.7518 3.0730 66.6253 0.3017 0.3370 NA NA NA NA cover
2020-02-27 TRUE SIM1 EOF SIM CCMT 0.0936 40 0.0960 60.0 189.00 TRUE 0.6470 1.0100 1.660 TRUE 0.471 TRUE 0.0081 TRUE 0.0007 TRUE 0.0352 FALSE -0.0314 TRUE 0.0102 114232.000 0.0926 0.0778 6.8539 0.1896 0.0538 15.1102 0.4180 0.1186 1.0574 0.0293 0.0083 NA NA NA NA cover
2020-02-27 TRUE SIM2 EOF SIM FBM 0.0919 40 0.1309 975.0 1350.00 TRUE 1.7700 2.5100 4.280 TRUE 2.890 TRUE -0.0397 TRUE 0.0114 TRUE 0.1140 FALSE -0.0356 TRUE 0.0890 130336.000 0.1057 0.0721 127.0776 0.5578 0.3767 280.1553 1.2298 0.8304 15.9270 0.0699 0.0472 NA NA NA NA cover
2020-03-05 TRUE ARR1 EOF ARR CCMT 0.0924 40 0.1100 440.0 692.00 TRUE 1.5300 1.1600 2.680 TRUE 2.070 TRUE -0.0157 TRUE 0.0177 TRUE 0.0522 FALSE -0.0312 TRUE 0.0507 142485.000 0.1155 0.1768 62.6934 0.3819 0.2949 138.2139 0.8418 0.6502 17.6293 0.1074 0.0829 NA NA NA NA cover
2020-03-05 TRUE ARR2 EOF ARR FBM 0.0949 40 0.1231 705.0 1250.00 TRUE 1.5700 2.1200 3.680 TRUE 3.590 TRUE -0.0164 TRUE 0.0427 TRUE 0.1410 FALSE -0.0305 TRUE 0.1395 80667.000 0.0654 0.1131 56.8702 0.2969 0.2896 125.3761 0.6544 0.6384 18.0657 0.0943 0.0920 NA NA NA NA cover
2020-03-05 TRUE CAR1 EOF CAR CCMT 0.0950 40 0.1022 180.0 191.00 TRUE 0.9100 2.1300 3.040 TRUE 1.670 TRUE -0.0082 TRUE 0.0744 TRUE 0.2140 FALSE -0.0302 TRUE 0.1890 2086630.000 1.6919 0.9080 375.5934 6.3434 3.4847 828.0332 13.9846 7.6823 37.0319 0.6254 0.3436 NA NA NA NA cover
2020-03-05 TRUE CAR2 EOF CAR FBM 0.0947 40 0.1100 382.5 562.00 TRUE 1.5300 1.7200 3.250 TRUE 2.250 TRUE -0.0047 TRUE 0.0491 TRUE 0.4200 FALSE -0.0343 TRUE 0.3950 2255954.000 1.8292 0.9381 862.9024 7.3319 5.0759 1902.3546 16.1638 11.1903 81.2972 0.6908 0.4782 NA NA NA NA cover
2020-03-05 TRUE DCDC1 EOF DCDC CCMT 0.0942 40 0.1027 212.5 327.00 TRUE 1.2600 1.2800 2.540 TRUE 1.890 TRUE -0.0330 TRUE 0.1060 TRUE 0.3800 FALSE -0.0314 TRUE 0.3785 575089.000 0.4663 0.2752 122.2064 1.4607 1.0869 269.4163 3.2203 2.3962 13.2522 0.1584 0.1179 NA NA NA NA cover
2020-03-05 TRUE DCDC2 EOF DCDC FBM 0.0942 40 0.1059 292.5 420.00 TRUE 2.1200 1.0700 3.180 TRUE 1.770 TRUE -0.0042 TRUE 0.0671 TRUE 0.8790 FALSE -0.0320 TRUE 0.8775 667570.000 0.5413 0.3133 195.2642 2.1229 1.1816 430.4795 4.6801 2.6050 20.7660 0.2258 0.1257 NA NA NA NA cover
2020-03-05 TRUE MOS1 EOF MOS CCMT 0.0913 40 0.1097 460.0 842.00 TRUE 1.3000 2.0300 3.340 TRUE 3.130 TRUE -0.0139 TRUE 0.0884 TRUE 0.1210 FALSE -0.0317 TRUE 0.1195 325831.000 0.2642 0.1649 149.8823 1.0883 1.0199 330.4304 2.3992 2.2484 17.1831 0.1248 0.1169 NA NA NA NA cover
2020-03-05 TRUE MOS2 EOF MOS FBM 0.0954 40 0.1141 467.5 815.00 TRUE 1.5500 1.5700 3.120 TRUE 2.700 TRUE -0.0081 TRUE 0.0315 TRUE 0.3820 FALSE -0.0370 TRUE 0.3805 82189.000 0.0666 0.0415 38.4234 0.2564 0.2219 84.7081 0.5653 0.4892 4.3981 0.0294 0.0254 NA NA NA NA cover
2020-03-05 TRUE MUR1 EOF MUR CCMT 0.0962 40 0.1203 602.5 912.00 TRUE 4.4700 1.5800 6.060 TRUE 3.490 TRUE 0.0106 TRUE 0.1010 TRUE 2.4500 FALSE -0.0307 TRUE 2.4250 1517929.000 1.2308 0.7757 914.5522 9.1986 5.2976 2016.2218 20.2793 11.6790 105.8940 1.0651 0.6134 NA NA NA NA cover
2020-03-05 TRUE MUR2 EOF MUR FBM 0.0923 40 0.1233 775.0 1406.00 TRUE 4.4100 1.4300 5.840 TRUE 3.780 TRUE 0.0338 TRUE 0.0827 TRUE 2.4500 FALSE -0.0276 TRUE 2.4250 11920.000 0.0097 0.0071 9.2380 0.0696 0.0451 20.3661 0.1535 0.0993 1.2626 0.0095 0.0062 NA NA NA NA cover
2020-03-05 TRUE PB INST NA NA 0.0942 40 0.1136 485.0 972.00 TRUE 2.2900 1.1900 3.480 TRUE 3.270 TRUE -0.0039 TRUE 0.0870 TRUE 0.5540 FALSE -0.0330 TRUE 0.5525 NA NA NA NA NA NA NA NA NA NA NA NA 9.40 97.8 865.6 17.4 cover
2020-03-05 TRUE PBR1 EOF PBR CCMT 0.0938 40 0.1023 212.5 231.00 TRUE 0.6410 1.0500 1.690 TRUE 1.630 TRUE -0.0306 TRUE 0.0737 TRUE 0.0594 FALSE -0.0316 TRUE 0.0579 883190.000 0.7161 0.1640 187.6779 1.4926 1.4396 413.7546 3.2906 3.1737 7.8976 0.0628 0.0606 NA NA NA NA cover
2020-03-05 TRUE PBR2 EOF PBR FBM 0.0950 40 0.1027 192.5 248.00 TRUE 0.5730 1.2800 1.850 TRUE 1.620 TRUE -0.0186 TRUE 0.0281 TRUE 0.1040 FALSE -0.0361 TRUE 0.1025 94386.000 0.0765 0.0384 18.1693 0.1746 0.1529 40.0560 0.3850 0.3371 1.6767 0.0161 0.0141 NA NA NA NA cover
2020-03-05 TRUE SIM1 EOF SIM CCMT 0.0962 40 0.1002 100.0 177.00 TRUE 0.6720 0.7660 1.440 TRUE 0.719 TRUE 0.0051 TRUE 0.0102 TRUE 0.0945 FALSE -0.0333 TRUE 0.0695 712603.000 0.5778 0.4852 71.2603 1.0261 0.5124 157.1005 2.2622 1.1296 10.9937 0.1583 0.0790 NA NA NA NA cover
2020-03-05 TRUE SIM2 EOF SIM FBM 0.0924 40 0.1039 287.5 509.00 TRUE 1.5600 0.7030 2.260 TRUE 1.130 TRUE 0.0136 TRUE 0.0091 TRUE 0.6360 FALSE -0.0344 TRUE 0.6110 819814.000 0.6647 0.4535 235.6965 1.8528 0.9264 519.6166 4.0846 2.0423 29.5405 0.2322 0.1161 NA NA NA NA cover
2020-03-05 TRUE STU1 EOF STU CCMT 0.0943 40 0.1082 347.5 643.00 TRUE 1.3300 0.6440 1.980 TRUE 2.280 TRUE -0.0246 TRUE 0.0625 TRUE 0.0353 FALSE -0.0316 TRUE 0.0338 868843.000 0.7045 0.2821 301.9229 1.7203 1.9810 665.6193 3.7926 4.3672 22.2095 0.1265 0.1457 NA NA NA NA cover
2020-03-05 TRUE STU2 EOF STU FBM 0.0969 40 0.1287 795.0 864.00 TRUE 1.7400 2.1100 3.840 TRUE 3.900 TRUE -0.0250 TRUE 0.0612 TRUE 0.2550 FALSE -0.0321 TRUE 0.2535 131119.000 0.1063 0.0805 104.2396 0.5035 0.5114 229.8066 1.1100 1.1274 14.4988 0.0700 0.0711 NA NA NA NA cover
2020-03-10 TRUE ARR1 EOF ARR CCMT 0.0916 40 0.1070 385.0 483.00 TRUE 1.0800 1.4300 2.500 TRUE 2.140 TRUE 0.2700 TRUE 0.0168 TRUE 0.0417 FALSE -0.0219 TRUE 0.0402 63574.000 0.0515 0.0789 24.4760 0.1589 0.1360 53.9598 0.3504 0.2999 6.8826 0.0447 0.0383 NA NA NA NA cover
2020-03-10 TRUE DCDC1 EOF DCDC CCMT 0.0924 40 0.0988 160.0 266.00 TRUE 0.7660 1.1800 1.950 TRUE 1.630 TRUE -0.0271 TRUE 0.1090 TRUE 0.1860 FALSE -0.0326 TRUE 0.1845 360865.000 0.2926 0.1727 57.7384 0.7037 0.5882 127.2901 1.5513 1.2968 6.2612 0.0763 0.0638 NA NA NA NA cover
2020-03-10 TRUE DCDC2 EOF DCDC FBM 0.0935 40 0.1043 270.0 402.00 TRUE 1.4600 1.0900 2.540 TRUE 1.880 TRUE -0.0263 TRUE 0.0749 TRUE 0.5020 FALSE -0.0338 TRUE 0.5005 545401.000 0.4422 0.2560 147.2583 1.3853 1.0254 324.6456 3.0541 2.2605 15.6607 0.1473 0.1090 NA NA NA NA cover
2020-03-10 TRUE MOS1 EOF MOS CCMT 0.0921 40 0.1017 240.0 384.00 TRUE 0.7930 1.3800 2.170 TRUE 2.360 TRUE 0.0123 TRUE 0.1280 TRUE 0.0357 FALSE -0.0317 TRUE 0.0342 326572.000 0.2648 0.1652 78.3773 0.7087 0.7707 172.7906 1.5623 1.6991 8.9855 0.0812 0.0884 NA NA NA NA cover
2020-03-10 TRUE MOS2 EOF MOS FBM 0.0947 40 0.1090 357.5 518.00 TRUE 0.9360 1.3300 2.270 TRUE 2.000 TRUE -0.0315 TRUE 0.0356 TRUE 0.1630 FALSE -0.0320 TRUE 0.1615 22553.000 0.0183 0.0114 8.0627 0.0512 0.0451 17.7750 0.1129 0.0994 0.9229 0.0059 0.0052 NA NA NA NA cover
2020-03-10 TRUE PBR1 EOF PBR CCMT 0.0926 40 0.0994 170.0 157.00 TRUE 0.5380 0.6440 1.180 TRUE 1.370 TRUE -0.0172 TRUE 0.0997 TRUE 0.0373 FALSE -0.0302 TRUE 0.0358 307367.000 0.2492 0.0571 52.2524 0.3627 0.4211 115.1956 0.7996 0.9283 2.1988 0.0153 0.0177 NA NA NA NA cover
2020-03-10 TRUE PBR2 EOF PBR FBM 0.0915 40 0.1044 322.5 346.00 TRUE 0.5220 1.6800 2.200 TRUE 1.940 TRUE -0.0225 TRUE 0.0335 TRUE 0.0290 FALSE -0.0315 TRUE 0.0275 40670.000 0.0330 0.0166 13.1161 0.0895 0.0789 28.9157 0.1973 0.1739 1.2104 0.0083 0.0073 NA NA NA NA cover
2020-03-10 TRUE STU1 EOF STU CCMT 0.0930 40 0.1052 305.0 468.00 TRUE 1.0800 0.2410 1.320 TRUE 1.970 TRUE -0.0174 TRUE 0.1080 TRUE 0.0356 FALSE -0.0325 TRUE 0.0341 271959.000 0.2205 0.0883 82.9475 0.3590 0.5358 182.8660 0.7914 1.1811 6.1016 0.0264 0.0394 NA NA NA NA cover
2020-03-10 TRUE STU2 EOF STU FBM 0.0948 40 0.1296 870.0 882.00 TRUE 1.1700 1.0500 2.220 TRUE 3.060 TRUE -0.0187 TRUE 0.0384 TRUE 0.1160 FALSE -0.0312 TRUE 0.1145 17776.000 0.0144 0.0109 15.4651 0.0395 0.0544 34.0944 0.0870 0.1199 2.1511 0.0055 0.0076 NA NA NA NA cover
2020-03-12 TRUE MUR1 EOF MUR CCMT 0.0928 40 0.1144 540.0 865.00 TRUE 3.4800 1.7400 5.220 TRUE 3.550 TRUE 0.0118 TRUE 0.1170 TRUE 1.4400 FALSE -0.0310 TRUE 1.4150 97219.000 0.0788 0.0497 52.4983 0.5075 0.3451 115.7377 1.1188 0.7609 6.0787 0.0588 0.0400 NA NA NA NA cover
2020-03-12 TRUE MUR2 EOF MUR FBM 0.0924 40 0.1208 710.0 952.00 TRUE 2.9800 0.1330 3.110 TRUE 3.970 TRUE -0.0099 TRUE 0.0844 TRUE 0.9920 FALSE -0.0310 TRUE 0.9670 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA cover
2020-03-12 TRUE SIM1 EOF SIM CCMT 0.0922 40 0.0940 45.0 70.10 TRUE 2.1200 1.5800 3.710 TRUE 0.694 TRUE 0.0409 TRUE 0.0170 TRUE 1.1900 FALSE -0.0319 TRUE 1.1650 65977.000 0.0535 0.0449 2.9690 0.2448 0.0458 6.5454 0.5396 0.1009 0.4580 0.0378 0.0071 NA NA NA NA cover

2 Quality Assurance

Next we want to evaluate all the controls we put in place to make sure our data is sound. These included labratory standards and standard operating procedures. If the minimum amount of quality objectives (80%) were not met for for each sampling trip the values will be dropped and not considered for analysis.

2.1 Standard checks

First, we will evaluate the logical for the overall trip objectives.

conc <- c(10,11,13:15,17,19,21,23,25,27,31:39)
cat(paste0("`", names(dat[conc]), "`   "), sep = "", fill = TRUE)

TSS.mgl TUR.ntu NO3.NO2.mgl TKN.mgl TN.mgl TIP.mgl
NH3.mgl OrthoP.mgl NOx.mgl NO2.mgl NO3.mgl TSS.kg
TN.kg TIP.kg TSS.lb TN.lb TIP.lb TSS.lbac TN.lbac
TIP.lbac

for (i in conc) {
  dat[,i] <- ifelse(
    dat[,2] == FALSE,
    NA,
    dat[,i]
  )
}

This will replace concentration and load data in the above columns with “NA” where the logical in column “qaqc.check” equals “FALSE” for their respective records.

After that we are going to evaluate the the labratory standards used during each analysis batch. Here the code looks to in the individual analytes and their respective logical checks. Generally this is in the neighboring column. The exception is the NO3.mgl column; this checks against the NOx.mgl standard.

logic <- c(12, 16, 18, 20, 22, 24, 26)
for (i in logic) {
  dat[,i - 1] <- ifelse(
    dat[,i] == FALSE,
    NA,
    dat[,i - 1]
  )
}

dat[,27] <- ifelse(
  dat[,24] == FALSE,
  NA,
  dat[,27]
)

This step leaves us with a data set where any nutrient concentration values which don’t meet our quality standard are omitted. This step is then repeated to omit loads which are associated with these omitted records.

# replace tss loads
for (i in c(21, 24, 27)) { 
  dat[,10 + i] <- ifelse(
    is.na(dat[,10]) == TRUE,
    NA,
    dat[,10 + i]
  )
}
# replace tn loads
for (i in c(17, 20, 23)) { 
  dat[,15 + i] <- ifelse(
    is.na(dat[,15]) == TRUE,
    NA,
    dat[,15 + i]
  )
}
# replace tip loads
for (i in c(16, 19, 22)) { 
  dat[,17 + i] <- ifelse(
    is.na(dat[,17]) == TRUE,
    NA,
    dat[,17 + i]
  )
}

We then remove the logical columns in our next little bit of housekeeping.

dat <- dat %>% 
  select(-c(2, 12, 16, 18, 20, 22, 24, 26))

rm(conc, i, logic)

2.2 Impute missing values

Now that we have omitted values that were not up to our quality standards we will use a correlation method to impute those values missing from our data set.

Sediment bound and associated nutrients are grouped together.

impdat <-
  mice(
    data = dat[,c(9, 10, 14)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )

set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))
# randomly select imputed dataset and combine with complete dataset

# inspect imputed data
# imputed datasets in magenta; observed in blue. are values plausible?
#stripplot(impdat)
# do imputed points fall in likely area of distrib.?

dat[,c(9, 10, 14)] <- compdat[,1:ncol(compdat)]

Orthophosphate is grouped with Total Inorganic Phosphorus

impdat <-
  mice(
    data = dat[,c(14, 16)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )

set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))
# randomly select imputed dataset and combine with complete dataset

# inspect imputed data
# imputed datasets in magenta; observed in blue. are values plausible?
#stripplot(impdat)
# do imputed points fall in likely area of distrib.?

dat[,c(14, 16)] <- compdat[,1:ncol(compdat)]

Nitrogen and associated complexes grouped together.

#PerformanceAnalytics::chart.Correlation(dat[,c(11:13, 15, 17:19)])
#PerformanceAnalytics::chart.Correlation(dat[,c(11:12, 15, 17)])
# NO3NO2 - NOx - NO3
# TKN - TN
# NH3 - TN
# NOx - NO3NO2
# NO3 - NOx
 
impdat <-
  mice(
    data = dat[,c(11:12, 15, 17)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )
 
#summary(impdat)
 
set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))
 
dat[,c(11:12, 15, 17)] <- compdat[,1:ncol(compdat)]
 
# ..TN ------------------------------------------------------------
 
#PerformanceAnalytics::chart.Correlation(dat[,c(11:13, 15, 17:19)])

impdat <-
  mice(
    data = dat[,c(11:13, 15, 17)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )
 
#summary(impdat)
 
set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))

dat[,13] <- compdat$TN.mgl
 
# NO3 ------------------------------------------
 
#PerformanceAnalytics::chart.Correlation(dat[,c(11:12, 15, 17, 19)])
 
impdat <-
  mice(
    data = dat[,c(11:12, 15, 19)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )
 
#summary(impdat)
 
set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))

# inspect imputed data
# imputed datasets in magenta; observed in blue. are values plausible?
stripplot(impdat)

  # do imputed points fall in likely area of distrib.?
 
dat[,c(11:12, 15, 19)] <- compdat[,1:ncol(compdat)]

This should leave us with a data set that has values removed for QA then imputed based on their correlation to other analytes in the data set.

2.3 Method detection limits

Here we want to correct any concentration values that are below our method detection limits. When less than 5% of the data set, values below our method detection limits are replaced with half the MDL.

if (sum(dat$TSS.mgl < 5, na.rm = TRUE) / sum(!is.na(dat$TSS.mgl)) < 0.05) {
  print("Less than 5% of TSS values are below MDL")
  print(sum(dat$TSS.mgl < 5, na.rm = TRUE) / sum(!is.na(dat$TSS.mgl)) *100)
  dat <- dat %>% mutate(TSS.mgl = replace(TSS.mgl, TSS.mgl < 5, 5/2))
} else {
  print("More than 5% of TSS values are below MDL and")
  print("the values have remained unchanged")
  print(dat %>% count(TSS.mgl < 5))
  print(sum(dat$TSS.mgl < 5, na.rm = TRUE) / sum(!is.na(dat$TSS.mgl)) *100)}
## [1] "Less than 5% of TSS values are below MDL"
## [1] 0.6147541
## [1] "Less than 5% of TUR values are below MDL"
## [1] 0
## [1] "Less than 5% of NO3.NO2 values are below MDL"
## [1] 2.04918
## [1] "Less than 5% of TN values are below MDL"
## [1] 4.508197
## [1] "Less than 5% of TIP values are below MDL"
## [1] 0
## [1] "More than 5% of NH3 values are below MDL and"
## [1] "the values have remained unchanged"
##   NH3.mgl < 0.01   n
## 1          FALSE 403
## 2           TRUE  85
## [1] 17.41803
## [1] "Less than 5% of Ortho Phosphorus values are below MDL"
## [1] 2.868852
## [1] "Less than 5% of NOx values are below MDL"
## [1] 4.303279
## [1] "More than 5% of NO2 values are below MDL and"
## [1] "the values have remained unchanged"
##   NO2.mgl < 0.05   n
## 1          FALSE  27
## 2           TRUE 359
## 3             NA 102
## [1] 93.00518
## [1] "5% of NO3 values are below MDL"
## [1] 4.713115

Here we can see that most of our nitrite values are illogical and as such we will not be evaluating them henceforth. Further, ‘NO3.mgl’ is a calculated value based on these illogical ‘NO2.mgl’ values. We will only consider combined nitrate-nitrate as ‘NOx.mgl’ which was directly measured and generally met the standard outlined in the lachat operating procedure.

Here we need to make another round of imputed values for the large number of NH3 values that were either negative or below the method detection limit (16%). For this case we imputed values based on correlation to other variables rather than substituting 1/2 of the method detection limit. Further, we need to clean up the 9 illogical TKN values that are < 0.

#NH3 ---------------
 
dat$NH3.mgl <-
  ifelse(
    dat$NH3.mgl < .01,
    NA,
    dat$NH3.mgl
  )
 
impdat <-
  mice(
    data = dat[,c(11:13, 15, 17)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )
 
set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))
  # randomly select imputed dataset and combine with complete dataset
 
# inspect imputed data
# imputed datasets in magenta; observed in blue. are values plausible?
# stripplot(impdat)
  # do imputed points fall in likely area of distrib.?
 
dat[,c(11:13, 15, 17)] <- compdat[,1:ncol(compdat)]
 
# TKN-------------------
print(
  paste(
    sum(dat$TKN.mgl < 0, na.rm = TRUE) / sum(!is.na(dat$TKN.mgl)) *100,
    "% of TKN values are below 0"
  )
)
## [1] "1.84426229508197 % of TKN values are below 0"
dat$TKN.mgl <-
  ifelse(
    dat$TKN.mgl <= 0,
    NA,
    dat$TKN.mgl
  )
 
#summary(dat$TKN.mgl)
 
impdat <-
  mice(
    data = dat[,c(11:13, 15, 17)],
    m = 5,
    maxit = 50,
    method = 'pmm',
    seed = 1234,
    printFlag = FALSE
  )
 
set.seed(1234)  # set seed for random imputed dataset selection
compdat <- complete(impdat, round(runif(1, 1, 5), 0))
  # randomly select imputed dataset and combine with complete dataset
 
# inspect imputed data
# imputed datasets in magenta; observed in blue. are values plausible?
stripplot(impdat)

  # do imputed points fall in likely area of distrib.?
 
dat[,c(11:13, 15, 17)] <- compdat[,1:ncol(compdat)]

2.4 Calculate loads

Now that we’ve fixed any of our observations that were below our method detection limits we can calculate loads such that they will reflect those changes.

#removes loads that were previously calculated in excel
dat <- dat[-c(22:31)]

#introduces the area of the fields to the data set
a <- as.data.frame(cbind(c("ARR1", "ARR2",  "PBR1", "PBR2", "STU1", "STU2", "MOS1", "MOS2", "DCDC1",
             "DCDC2", "SCH1", "SCH2", "PRE1", "PRE2", "MUZ1", "MUZ2", "SIM1", "SIM2", "MUR1", "MUR2", "CAR1", "CAR2"),
          c(14.55, 15.48, 52.39, 23.89, 73.04, 34.24, 19.23, 19.26, 20.33,
            20.73, 10.38, 9.12, 36.62, 37.37, 19.29, 17.83, 14.29, 17.59, 19.04, 16.13, 22.36, 23.4)))
a <- as.data.frame(a) %>% 
  transform(V2= as.numeric(as.character(V2)))

dat <- merge(
  dat,
  a,
  by.x = "sampleid",
  by.y = "V1",
  all.x = TRUE,
  all.y = FALSE
)
names(dat)[names(dat) == "V2"] <- "acres"

# change acres where we switched fields
dat[dat$sampleid == "ARR1",]$acres <-
  ifelse(
    dat[dat$sampleid == "ARR1",]$Date >="2019-10-18",
    7.84, # New field size
    14.55   # old field size
  )

dat[dat$sampleid == "ARR2",]$acres <-
  ifelse(
    dat[dat$sampleid == "ARR2",]$Date >="2019-10-18",
    6.94, # New field size
    15.48   # old field size
  )

dat[dat$sampleid == "STU1",]$acres <-
  ifelse(
    dat[dat$sampleid == "STU1",]$Date >="2019-12-5",
    29.97, # New field size
    73.04   # old field size
  )

dat[dat$sampleid == "STU2",]$acres <-
  ifelse(
    dat[dat$sampleid == "STU2",]$Date >="2019-12-5",
    15.85, # New field size
    34.24   # old field size
  )

#rearrange columns so subsequent code doesn't get thrown off 
dat <- dat[c(2,1,3:27)]

###calculate loads
dat$in.runoff.ac <- dat$acft.discharge * 12 / dat$acres
dat$TSS.kg <- dat$TSS.mgl * dat$event.disch.l / 1000000
dat$TN.kg <- dat$TN.mgl * dat$event.disch.l / 1000000
dat$TIP.kg <- dat$TIP.mgl * dat$event.disch.l / 1000000
dat$TSS.lb <- dat$TSS.kg * 2.2046
dat$TN.lb <- dat$TN.kg * 2.2046
dat$TIP.lb <- dat$TIP.kg * 2.2046
dat$TSS.lbac <- dat$TSS.lb / dat$acres
dat$TN.lbac <- dat$TN.lb / dat$acres
dat$TIP.lbac <- dat$TIP.lb / dat$acres

#rearrange columns
dat <- dat[c(1:21,28:37,22:27)]

Now the data set has loads that reflect our changes resulting from our quality assurance, both MDL and standards.

3 The paired event data frame

This project is based on a paired field design. In preparation for later analysis we want to create another data frame that contains only events where the sampler on the treatment and the control field both sampled. We want to do this after QA so the dat.pair reflects any changes we made above.

dupedates <- function(data) {
  filter(data,
         duplicated(Date)|duplicated(Date, fromLast = TRUE) == TRUE
  )
}                                                               

'%=%' = function(l, r, ...) UseMethod('%=%')                                                    

'%=%.lbunch' = function(l, r, ...) {
  Envir = as.environment(-1)
  
  if (length(r) > length(l))
    warning("RHS has more args than LHS. Only first", length(l), "used.")
  
  if (length(l) > length(r))  {
    warning("LHS has more args than RHS. RHS will be repeated.")
    r <- extendToMatch(r, l)
  }
  
  for (II in 1:length(l)) {
    do.call('<-', list(l[[II]], r[[II]]), envir=Envir)
  }
} 

#....Grouping the left hand side
g = function(...) {
  List = as.list(substitute(list(...)))[-1L]
  class(List) = 'lbunch'
  return(List)
}

#....Assigning and finding duplicate dates
g(arr, car, dcdc, mos, mur, muz, sch, sim, stu, pbr, pre) %=% list(
  subset(dat, farm == "ARR") %>% 
    dupedates(),
  subset(dat, farm == "CAR") %>% 
    dupedates(),
  subset(dat, farm == "DCDC") %>% 
    dupedates(),
  subset(dat, farm == "MOS") %>% 
    dupedates(),
  subset(dat, farm == "MUR") %>% 
    dupedates(),
  subset(dat, farm == "MUZ") %>% 
    dupedates(),
  subset(dat, farm == "SCH") %>% 
    dupedates(),
  subset(dat, farm == "SIM") %>% 
    dupedates(),
  subset(dat, farm == "STU") %>% 
    dupedates(),
  subset(dat, farm == "PBR") %>% 
    dupedates(),
  subset(dat, farm == "PRE") %>% 
    dupedates()
)

#..Combining all of the these into one data frame and cleaning the environment
dat.pair <- rbind(arr, car, dcdc, mos, mur, muz, sch, sim, stu, pbr, pre)
  # Combines all the individual farm data frames into
rm(arr, car, dcdc, mos, mur, muz, sch, sim, stu, pbr, pre)
  # removes the farm data frames

and how about a looksy

dat.pair <- dat.pair[ order(dat.pair$Date, dat.pair$sampleid),]
kable(tail(dat.pair[,c(1:5,9:11)]), caption = "Table 3.1: Example of 'dat.pair'") %>% 
  kable_paper() %>% 
  remove_column(1)
Table 3.1: Example of ‘dat.pair’
Date sampleid sample.type farm treatment TSS.mgl TUR.ntu NO3.NO2.mgl
2020-03-10 PBR1 EOF PBR CCMT 170.0 157 0.538
2020-03-10 PBR2 EOF PBR FBM 322.5 346 0.522
2020-03-10 STU1 EOF STU CCMT 305.0 468 1.080
2020-03-10 STU2 EOF STU FBM 870.0 882 1.170
2020-03-12 MUR1 EOF MUR CCMT 540.0 865 3.480
2020-03-12 MUR2 EOF MUR FBM 710.0 952 2.980

As you can see the data frame, dat.pair contains only records where samples were collected for both the treatment and control.

4 Reduction Potential

The next step we are going to tackle is calculating the reduction potential (or increase!) of the treatment. We do this by reducing the paired events into one record then subtracting the treatment value from the value of the control field. (FBM-CCMT) This difference is then considered relative to the control value as a percent reduction. +Positive values represent a reduction -Negative values represent negative reduction, ie an increase relative to the control.

# Now we use the paired dataframe to create this reduction potential dataframe.

# Here we create the new data frame and change the format of the paired data
# from a "long" format into a "wide" format so instead of every sample having
# its own row, the sample pairs each have their own row.
dat.reduct <- dat.pair %>% 
  pivot_wider(
    id_cols = c(Date, farm, season),
    names_from = treatment,
    names_sep = ".",
    # this is where you can add or remove columns you want to see.
    values_from = names(dat.pair[,c(9:31)])
  ) %>% 
  as.data.frame()

# This is the difference code.
for (i in 4:48) {
  if (i %% 2 == 0) {  
    dat.reduct[,ncol(dat.reduct) + 1] <- dat.reduct[,i + 1] - dat.reduct[,i]
    # This names the column from where the data was taken. 
    names(dat.reduct)[ncol(dat.reduct)] <- names(dat.reduct)[i]
    # the name is changed by replaceing "CCMT" with "dif" in the column title
    names(dat.reduct)[ncol(dat.reduct)] <- gsub(
      pattern = "CCMT",
      replacement = "dif",
      x = names(dat.reduct)[ncol(dat.reduct)]
    )
    # Then it moves to find the percent reduction in the same way as above. 
    dat.reduct[,ncol(dat.reduct) + 1] <- dat.reduct[,ncol(dat.reduct)] / dat.reduct[,i + 1] * 100
    names(dat.reduct)[ncol(dat.reduct)] <- names(dat.reduct)[i]
    names(dat.reduct)[ncol(dat.reduct)] <- gsub(
      pattern = "CCMT",
      replacement = "per",
      x = names(dat.reduct)[ncol(dat.reduct)]
    )
  }
}

kable(tail(dat.reduct[c(1,2,4,5,50,51,6,7,52,53)]), caption = "Table 4.1: Example of 'dat.reduct'", digits = 3) %>% 
  kable_paper() %>% remove_column(1)
Table 4.1: Example of ‘dat.reduct’
Date farm TSS.mgl.CCMT TSS.mgl.FBM TSS.mgl.dif TSS.mgl.per TUR.ntu.CCMT TUR.ntu.FBM TUR.ntu.dif TUR.ntu.per
2020-03-05 STU 347.5 795.0 447.5 56.289 643 864 221 25.579
2020-03-10 DCDC 160.0 270.0 110.0 40.741 266 402 136 33.831
2020-03-10 MOS 240.0 357.5 117.5 32.867 384 518 134 25.869
2020-03-10 PBR 170.0 322.5 152.5 47.287 157 346 189 54.624
2020-03-10 STU 305.0 870.0 565.0 64.943 468 882 414 46.939
2020-03-12 MUR 540.0 710.0 170.0 23.944 865 952 87 9.139

Now we have new columns with a .dif and .per suffix. These represent absolute difference and relative reduction respectively.
We will come back to these reduction potential and paired data frames in just a moment when we start to summarize and visualize our data.

5 Data summary

We now have much data to consider. Lets start with the basic stuff.

5.1 n=

# total number of samples
length(dat$sampleid)
## [1] 488
# number of samples by type: Edge-of-Field
dat$sample.type[dat$sample.type == "EOF"] %>% length()
## [1] 442
# number of samples by type: Instream
dat$sample.type[dat$sample.type == "INST"] %>% length()
## [1] 46
# number of samples by treatment: Cover Crop - Minimum Tillage
length(dat$treatment[!is.na(dat$treatment) & dat$treatment == "CCMT"])
## [1] 243
# number of samples by treatment: Farmer Best Management
length(dat$treatment[!is.na(dat$treatment) & dat$treatment == "FBM"])
## [1] 199
# number of EOF samples by season
length(dat$season[dat$sample.type == "EOF" & dat$season == "cover"])
## [1] 273
length(dat$season[dat$sample.type == "EOF" & dat$season == "cash"])
## [1] 169
# number of paired sample events
length(dat.pair$sampleid)/2
## [1] 158
# during the cover crop season
length(dat.pair$sampleid[dat.pair$season == "cover"])/2
## [1] 101
# during the cash crop season
length(dat.pair$sampleid[dat.pair$season == "cash"])/2
## [1] 57
dat$month <- month(dat$Date)
dat$year <- year(dat$Date)
df <- table(dat$year, dat$month)
  kable(df, col.names = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sept",
        "Oct", "Nov", "Dec"), caption = "Table 5.1 : Samples collected by month") %>% 
    kable_paper()
Table 5.1 : Samples collected by month
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
2018 0 45 27 10 15 11 26 0 11 4 7 6
2019 10 0 18 21 14 39 12 23 1 29 12 30
2020 46 42 29 0 0 0 0 0 0 0 0 0

5.2 Edge of Field samples

Lets take a look at some summary statistics for the analytes.

df <- list()

for(i in 9:17) {
  df1 <- mosaic::favstats(dat[dat$sample.type == "EOF",i])
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)
df <- df[,c(10,1:9)]
knitr::kable(df, caption = "Table 5.2: Statistical summary of nutrient concentrations (EOF only)", digits = 4,
            col.names = c('Analyte', 'min', 'Q1', 'Median', 'Q3', 'max', 'mean', 'std dev.', 'n=', 'na') ) %>% 
  kable_paper() %>% 
  remove_column(1)
Table 5.2: Statistical summary of nutrient concentrations (EOF only)
Analyte min Q1 Median Q3 max mean std dev. n= na
TSS.mgl 2.5000 270.5000 630.0000 1480.6250 11212.00 1339.9326 1866.3768 442 0
TUR.ntu 9.2300 252.5000 816.5000 1902.5000 10340.00 1568.3602 2145.8004 442 0
NO3.NO2.mgl 0.1150 1.0100 2.0650 3.7075 36.50 3.1639 3.6227 442 0
TKN.mgl 0.0270 0.7198 1.2600 2.4050 169.00 2.6503 9.1090 442 0
TN.mgl 0.5000 2.1075 3.5100 6.1250 181.00 5.7916 10.6983 442 0
TIP.mgl 0.0750 1.8725 3.2900 5.4150 49.50 4.8574 5.1151 442 0
NH3.mgl 0.0102 0.0442 0.0946 0.2445 16.30 0.3922 1.2452 442 0
OrthoP.mgl 0.0050 0.0754 0.1530 0.2977 7.02 0.3060 0.5369 442 0
NOx.mgl 0.0035 0.1430 0.4275 1.3025 30.90 1.4738 2.8758 442 0
Table 5.3: Statistical summary of nutrient concentrations from paired events (EOF only)
Analyte min Q1 Median Q3 max mean std dev. n= na
TSS.mgl 19.0000 285.1250 630.0000 1616.8750 11212.00 1333.1367 1831.0265 316 0
TUR.ntu 9.2300 265.0000 819.5000 1752.5000 10340.00 1586.4333 2158.9337 316 0
NO3.NO2.mgl 0.1150 0.9228 1.7850 3.5950 36.50 2.9533 3.5559 316 0
TKN.mgl 0.0320 0.6988 1.2550 2.5175 169.00 2.9396 10.6948 316 0
TN.mgl 0.5000 1.9475 3.2900 6.0525 181.00 5.8660 12.2658 316 0
TIP.mgl 0.2000 1.8575 3.2200 5.4400 21.20 4.6288 4.2038 316 0
NH3.mgl 0.0102 0.0403 0.0834 0.1977 16.30 0.3411 1.3305 316 0
OrthoP.mgl 0.0050 0.0716 0.1400 0.2580 2.39 0.2475 0.3408 316 0
NOx.mgl 0.0035 0.1280 0.3295 1.1550 30.90 1.4051 3.0194 316 0

and this same code can be run again to utilize dat.treatment as a factor.

df <- list()

for(i in c(9:17,22,29,30,31)) {
  df1 <- mosaic::favstats(dat[i] ~ dat$treatment)
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)
df <- df[,c(11,1:10)]
knitr::kable(df, caption = "Table 5.4: Statistical summary of analytes by treatment (EOF only)", digits = 4,
             col.names = c('Analyte', 'Treatment', 'min', 'Q1', 'Median', 'Q3', 'max', 'mean', 'std dev.', 'n=', 'na')) %>% 
  kable_paper() %>% 
  collapse_rows(1)
Table 5.4: Statistical summary of analytes by treatment (EOF only)
Analyte Treatment min Q1 Median Q3 max mean std dev. n= na
TSS.mgl CCMT 2.5000 206.7500 492.0000 1130.0000 11056.7000 1240.0519 1928.7611 243 0
FBM 2.5000 377.5000 835.0000 1960.0000 11212.0000 1461.8975 1784.4862 199 0
TUR.ntu CCMT 9.2300 184.5000 639.0000 1393.5000 9900.0000 1390.0697 2152.9275 243 0
FBM 9.2300 436.0000 952.0000 2240.6500 10340.0000 1786.0717 2122.1731 199 0
NO3.NO2.mgl CCMT 0.1150 0.9355 1.8800 3.7850 36.5000 3.2769 4.2602 243 0
FBM 0.1150 1.2200 2.3000 3.6550 16.3000 3.0260 2.6484 199 0
TKN.mgl CCMT 0.0320 0.7605 1.2300 2.2500 169.0000 2.8411 11.6290 243 0
FBM 0.0270 0.6810 1.2700 2.5700 45.5000 2.4173 4.4071 199 0
TN.mgl CCMT 0.5000 1.9300 3.3400 6.0650 181.0000 6.1093 13.4641 243 0
FBM 0.5000 2.4000 3.8100 6.2950 48.6000 5.4037 5.7514 199 0
TIP.mgl CCMT 0.0750 1.7200 3.0100 4.3700 49.5000 4.5371 5.4589 243 0
FBM 0.2000 2.0300 3.7800 7.0350 27.5000 5.2486 4.6446 199 0
NH3.mgl CCMT 0.0102 0.0482 0.1000 0.2700 16.3000 0.4322 1.4139 243 0
FBM 0.0106 0.0421 0.0834 0.2400 10.3000 0.3434 1.0027 199 0
OrthoP.mgl CCMT 0.0050 0.0804 0.1590 0.3740 7.0200 0.3524 0.6503 243 0
FBM 0.0050 0.0746 0.1430 0.2535 2.3900 0.2492 0.3455 199 0
NOx.mgl CCMT 0.0035 0.1225 0.3590 1.4800 30.9000 1.5910 3.2663 243 0
FBM 0.0035 0.1990 0.4560 1.2100 13.2000 1.3306 2.3115 199 0
in.runoff.ac CCMT 0.0006 0.0737 0.2643 0.6593 3.6195 0.4633 0.5702 224 19
FBM 0.0006 0.0599 0.2950 0.7238 4.3362 0.5213 0.6598 174 25
TSS.lbac CCMT 0.0032 7.1584 22.3401 76.0629 3213.3356 110.3339 303.7929 224 19
FBM 0.0027 9.4347 38.6530 128.5319 2633.0275 192.3576 432.5642 174 25
TN.lbac CCMT 0.0008 0.0545 0.1515 0.5091 20.8095 0.5543 1.5854 224 19
FBM 0.0010 0.0404 0.2271 0.6875 10.8072 0.7067 1.4067 174 25
TIP.lbac CCMT 0.0003 0.0493 0.1323 0.4041 11.1513 0.4358 0.9738 224 19
FBM 0.0007 0.0473 0.1846 0.5464 8.8128 0.6542 1.2569 174 25
Table 5.5: Statistical summary of analytes by treatment from paired events only (EOF only)
Analyte Treatment min Q1 Median Q3 max mean std dev. n= na
TSS.mgl CCMT 35.0000 216.0000 488.5000 1135.0000 11056.7000 1263.1044 1978.4335 158 0
FBM 19.0000 351.8750 811.2500 1962.5000 11212.0000 1403.1690 1674.0968 158 0
TUR.ntu CCMT 11.2000 191.0000 669.5000 1315.0000 9730.0000 1394.8975 2124.7912 158 0
FBM 9.2300 360.0000 912.5000 2340.0000 10340.0000 1777.9692 2182.4528 158 0
NO3.NO2.mgl CCMT 0.1150 0.8330 1.5450 3.4275 36.5000 3.0174 4.2941 158 0
FBM 0.1150 1.1600 2.1050 3.6050 16.3000 2.8892 2.6310 158 0
TKN.mgl CCMT 0.0961 0.7598 1.1700 2.5625 169.0000 3.4819 14.3585 158 0
FBM 0.0320 0.6795 1.2750 2.4275 45.5000 2.3972 4.7675 158 0
TN.mgl CCMT 0.5000 1.8050 3.0100 6.0575 181.0000 6.4816 16.2719 158 0
FBM 0.5000 2.3025 3.6850 5.9775 48.6000 5.2504 6.0266 158 0
TIP.mgl CCMT 0.4710 1.6975 2.9150 4.3750 19.4000 4.1592 4.1765 158 0
FBM 0.2000 2.0525 3.8550 7.0800 21.2000 5.0983 4.1916 158 0
NH3.mgl CCMT 0.0102 0.0473 0.0920 0.2220 16.3000 0.3983 1.6070 158 0
FBM 0.0106 0.0383 0.0753 0.1937 10.3000 0.2839 0.9812 158 0
OrthoP.mgl CCMT 0.0050 0.0739 0.1395 0.2960 2.3900 0.2530 0.3266 158 0
FBM 0.0050 0.0711 0.1400 0.2332 2.3900 0.2420 0.3553 158 0
NOx.mgl CCMT 0.0035 0.0969 0.2840 1.1700 30.9000 1.4615 3.5045 158 0
FBM 0.0035 0.1768 0.3935 1.1100 13.2000 1.3486 2.4503 158 0
in.runoff.ac CCMT 0.0038 0.1069 0.3292 0.7454 3.6195 0.5199 0.5764 147 11
FBM 0.0006 0.0670 0.2950 0.6821 3.2288 0.4844 0.5685 136 22
TSS.lbac CCMT 0.4688 8.6006 36.7931 93.5945 3213.3356 125.0021 321.3694 147 11
FBM 0.3733 9.3144 40.2174 115.1128 2536.3548 171.3839 381.7160 136 22
TN.lbac CCMT 0.0061 0.0610 0.1584 0.5771 20.8095 0.6718 1.9156 147 11
FBM 0.0010 0.0427 0.2271 0.5877 8.9791 0.6050 1.1611 136 22
TIP.lbac CCMT 0.0037 0.0628 0.1597 0.4664 11.1513 0.4833 1.0796 147 11
FBM 0.0010 0.0490 0.1907 0.5023 7.1915 0.5842 1.0310 136 22

While we have imputed any missing values for nutrient concentration, nutrient loads will still have some na values that result from missing data from our ultrasonic velocity meter which calculates discharge.

5.3 Instream samples

Lets have a look at the summary stats of nutrient concentrations for specifically the instream monitoring sites.

df <- list()

for(i in c(9:17,32,33,35)) {
  df1 <- mosaic::favstats(dat[dat$sample.type == "INST",i])
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)
df <- df[,c(10,1:9)]
knitr::kable(df, caption = "Table 5.6: Statistical summary of nutrient concentrations at instream monitoring sites (INST only)", digits = 2,
            col.names = c('Analyte', 'min', 'Q1', 'Median', 'Q3', 'max', 'mean', 'std dev.', 'n=', 'na') ) %>% 
  kable_paper() %>% 
  remove_column(1)
Table 5.6: Statistical summary of nutrient concentrations at instream monitoring sites (INST only)
Analyte min Q1 Median Q3 max mean std dev. n= na
TSS.mgl 2.50 38.45 105.65 235.98 1385.70 195.23 248.21 46 0
TUR.ntu 11.20 59.95 167.50 447.75 2280.00 332.16 427.44 46 0
NO3.NO2.mgl 0.47 0.72 1.13 1.92 7.68 1.59 1.37 46 0
TKN.mgl 0.04 0.45 0.61 0.84 2.96 0.76 0.59 46 0
TN.mgl 0.50 1.39 1.75 2.73 8.95 2.35 1.75 46 0
TIP.mgl 0.56 1.15 1.62 2.48 4.64 1.87 0.96 46 0
NH3.mgl 0.02 0.06 0.13 0.24 1.59 0.23 0.31 46 0
OrthoP.mgl 0.04 0.14 0.24 0.47 1.37 0.35 0.31 46 0
NOx.mgl 0.00 0.11 0.34 1.00 8.79 0.84 1.45 46 0
dissolvedO2.mg.l 5.19 7.00 8.90 10.12 13.38 8.89 2.26 46 0
dissolvedO2.sat.per 57.10 74.80 85.25 93.47 175.40 85.98 18.73 46 0
watertemp.c 1.60 8.65 14.10 20.62 34.90 15.34 8.98 46 0
df <- list()

for(i in c(9:17,32,33,35)) {
  df1 <- mosaic::favstats(dat[dat$sample.type == "INST",i] ~ dat$sampleid[dat$sample.type == "INST"])
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)

df <- df[,c(11,1:10)]
df <- remove_missing(df)
knitr::kable(df, caption = "Table 5.7: Statistical summary of nutrient concentrations at instream monitoring sites (Harris Bayou tributary and Porter Bayou)", digits = 2,
            col.names = c('Analyte','site', 'min', 'Q1', 'Median', 'Q3', 'max',
                          'mean', 'std dev.', 'n=', 'na') 
            ) %>% 
  kable_paper() %>% 
  remove_column(1) %>% 
  collapse_rows(1)
Table 5.7: Statistical summary of nutrient concentrations at instream monitoring sites (Harris Bayou tributary and Porter Bayou)
Analyte site min Q1 Median Q3 max mean std dev. n= na
TSS.mgl HB 2.50 20.25 39.40 73.12 179.50 53.78 46.20 22 0
PB 37.00 168.00 235.65 457.25 1385.70 324.90 286.20 24 0
TUR.ntu HB 11.20 32.42 58.55 96.40 246.00 78.37 66.08 22 0
PB 69.60 257.25 426.50 779.50 2280.00 564.80 485.18 24 0
NO3.NO2.mgl HB 0.54 0.62 0.73 1.14 7.68 1.31 1.69 22 0
PB 0.47 1.00 1.71 2.37 4.23 1.85 0.95 24 0
TKN.mgl HB 0.12 0.43 0.61 0.77 1.27 0.60 0.27 22 0
PB 0.04 0.46 0.64 1.17 2.96 0.91 0.76 24 0
TN.mgl HB 0.50 1.15 1.46 1.60 8.95 1.87 1.87 22 0
PB 0.50 1.83 2.62 3.21 7.19 2.79 1.53 24 0
TIP.mgl HB 0.56 1.01 1.21 1.76 3.08 1.43 0.69 22 0
PB 0.82 1.57 2.04 3.05 4.64 2.27 1.02 24 0
NH3.mgl HB 0.02 0.05 0.11 0.17 1.59 0.18 0.32 22 0
PB 0.02 0.08 0.21 0.30 1.15 0.28 0.30 24 0
OrthoP.mgl HB 0.04 0.17 0.27 0.52 1.37 0.41 0.36 22 0
PB 0.05 0.13 0.19 0.37 0.96 0.29 0.25 24 0
NOx.mgl HB 0.00 0.07 0.11 0.39 8.79 0.78 1.96 22 0
PB 0.00 0.28 0.71 1.17 3.00 0.90 0.77 24 0
dissolvedO2.mg.l HB 5.19 7.35 9.05 11.31 13.38 9.28 2.44 22 0
PB 5.71 7.02 8.32 9.74 13.03 8.54 2.07 24 0
dissolvedO2.sat.per HB 62.80 82.00 87.55 93.47 100.20 85.40 11.65 22 0
PB 57.10 74.25 83.05 92.67 175.40 86.52 23.70 24 0
watertemp.c HB 1.60 8.45 13.20 18.50 27.30 13.57 7.81 22 0
PB 4.00 9.65 15.35 24.82 34.90 16.95 9.82 24 0
df <- list()

for(i in 9:17) {
  df1 <- mosaic::favstats(dat[i] ~ dat$sample.type)
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)
df <- df[,c(11,1:10)]
knitr::kable(df, caption = "Table 5.8: Comparing nutrients concentration vaules between our sample types (Edge of Field and Instream)", digits = 4,
             col.names = c('Analyte', 'Treatment', 'min', 'Q1', 'Median', 'Q3', 'max', 'mean', 'std dev.', 'n=', 'na')) %>% 
  kable_paper() %>% 
  collapse_rows(1)
Table 5.8: Comparing nutrients concentration vaules between our sample types (Edge of Field and Instream)
Analyte Treatment min Q1 Median Q3 max mean std dev. n= na
TSS.mgl EOF 2.5000 270.5000 630.0000 1480.6250 11212.00 1339.9326 1866.3768 442 0
INST 2.5000 38.4500 105.6500 235.9750 1385.70 195.2304 248.2139 46 0
TUR.ntu EOF 9.2300 252.5000 816.5000 1902.5000 10340.00 1568.3602 2145.8004 442 0
INST 11.2000 59.9500 167.5000 447.7500 2280.00 332.1630 427.4404 46 0
NO3.NO2.mgl EOF 0.1150 1.0100 2.0650 3.7075 36.50 3.1639 3.6227 442 0
INST 0.4660 0.7220 1.1300 1.9175 7.68 1.5937 1.3655 46 0
TKN.mgl EOF 0.0270 0.7198 1.2600 2.4050 169.00 2.6503 9.1090 442 0
INST 0.0428 0.4510 0.6115 0.8420 2.96 0.7629 0.5940 46 0
TN.mgl EOF 0.5000 2.1075 3.5100 6.1250 181.00 5.7916 10.6983 442 0
INST 0.5000 1.3850 1.7550 2.7325 8.95 2.3498 1.7457 46 0
TIP.mgl EOF 0.0750 1.8725 3.2900 5.4150 49.50 4.8574 5.1151 442 0
INST 0.5550 1.1525 1.6200 2.4825 4.64 1.8682 0.9621 46 0
NH3.mgl EOF 0.0102 0.0442 0.0946 0.2445 16.30 0.3922 1.2452 442 0
INST 0.0163 0.0606 0.1320 0.2422 1.59 0.2322 0.3111 46 0
OrthoP.mgl EOF 0.0050 0.0754 0.1530 0.2977 7.02 0.3060 0.5369 442 0
INST 0.0433 0.1445 0.2360 0.4655 1.37 0.3497 0.3082 46 0
NOx.mgl EOF 0.0035 0.1430 0.4275 1.3025 30.90 1.4738 2.8758 442 0
INST 0.0035 0.1052 0.3370 1.0005 8.79 0.8408 1.4496 46 0

6 Visualization

6.1 Sample Locations

Here are a few maps that illustrate where our sampling locations are relative to the MS Delta and the Big Sunflower river. Skelton and the usgs sites are where there is ongoing sampling the others were included in the DeltaFARM and NIFA projects.
Porter Bayou near Shaw, MS

Porter Bayou near Shaw, MS

6.2 Concentration Distributions

6.2.1 Normality

Is our data normally distributed? I would guess not but lets make sure. Log transformed data shown with normal curve in red.

for(i in c(9:17, 20:22)) {
  d1 <- ggdensity(dat[dat$sample.type == "EOF", i],
                xlab = names(dat[i]))
  d2 <- ggdensity(log(dat[dat$sample.type == "EOF", i]),
                xlab = paste("log transformed", names(dat[i]))) +
    stat_overlay_normal_density(color="red")
print(d1)
print(d2)
  }
Figure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normalityFigure 6.1: Density plot to asses normality

Figure 6.1: Density plot to asses normality

Although we can see from the distrubutions, lets run a normality test on the various analyte distributions for verification.

df <- list()

for(i in c(9:17, 20:22)) {
  df1 <-shapiro.test(dat[dat$sample.type == "EOF",i])
  df1$i <- names(dat[i])
  df[[i -8]] <- df1
}
df <- data.frame(matrix(unlist(df), nrow = 12, byrow = T), stringsAsFactors = FALSE)
  
df <- df[,c(3,5,1,2)]
kable(df, digits = 5, caption = "Table 6.1: Shapiro-Wilk normality test results", col.names = c("Test","Analyte", "Test Statistic", "P-value")) %>% 
  kable_paper() %>% 
  collapse_rows(1)
Table 6.1: Shapiro-Wilk normality test results
Test Analyte Test Statistic P-value
Shapiro-Wilk normality test TSS.mgl 0.660096482233668 9.42162292687065e-29
TUR.ntu 0.681094814405459 5.09830639247152e-28
NO3.NO2.mgl 0.667718809245423 1.72220324984397e-28
TKN.mgl 0.166886521534146 4.0179470787522e-40
TN.mgl 0.320699738099478 2.32736118788988e-37
TIP.mgl 0.687953491789984 9.01893123687923e-28
NH3.mgl 0.278670484640589 3.67204715630481e-38
OrthoP.mgl 0.468963239901255 3.65748051409427e-34
NOx.mgl 0.516329848703278 5.45558665488862e-33
event.disch.l 0.753397619608873 6.02409696855267e-24
acft.discharge 0.753397619579854 6.02409695148469e-24
in.runoff.ac 0.747059562806752 3.26402338579999e-24

None of the anlayte values follow a normal distribution.

6.2.2 Anlayte concentrations by treatment and across time

Tables 5.2-8 nicely summarize our variable distributions yet plotting these can prove more meaningful, or at least better illustrate them. Here we want to understand several factors that we have established already: entire data, paired data points, and events that occured during our cover crop season, as well as paired events during the cover season. As we have established that our data in non-normal, i went ahead and superimposed the results for a two sided rank sum test. A p-value less than 0.05 would indicate that we can reject the null hypothesis that these samples are from the same population. In lower plot a black bar represents the median value and blue line is a locally smoothed regression line to aid in seeing trend over time. (method= loess())

p1 <- ggplot(dat[dat$sample.type == "EOF",], 
             aes(y= TSS.mgl, x= "All year", colour= treatment))+
  geom_boxplot(outlier.shape = NA )+
  coord_cartesian(ylim= c(0,5000))+
  stat_compare_means(
    aes(label = paste0(..method.., "\n", "p =", ..p.format..)),
    label.y = 3800)+
  theme(axis.title.x = element_blank())

p2 <- ggplot(dat.pair[dat.pair$sample.type == "EOF",], 
             aes(y= TSS.mgl, x= " paired All year", colour= treatment))+
  geom_boxplot(outlier.shape = NA)+
  coord_cartesian(ylim= c(0,5000))+
  stat_compare_means(
    aes(label = paste0(..method.., "\n", "p =", ..p.format..)),
    label.y = 3800)+
  theme(axis.title.y = element_blank(), axis.title.x = element_blank())

p3 <- ggplot(dat[dat$sample.type == "EOF" & dat$season == "cover",], 
             aes(y= TSS.mgl, x= "Cover season", colour= treatment))+
  geom_boxplot(outlier.shape = NA)+
  coord_cartesian(ylim= c(0,5000))+
  stat_compare_means(
    aes(label = paste0(..method.., "\n", "p =", ..p.format..)),
    label.y = 3800)+
  theme(axis.title.y = element_blank(), axis.title.x = element_blank())

p4 <- ggplot(dat.pair[dat.pair$sample.type == "EOF" & dat.pair$season == "cover",], 
             aes(y= TSS.mgl, x= "paired Cover season", colour= treatment))+
  geom_boxplot(outlier.shape = NA)+
  coord_cartesian(ylim= c(0,5000))+
  stat_compare_means(
    aes(label = paste0(..method.., "\n", "p =", ..p.format..)),
    label.y = 3800)+
  theme(axis.title.y = element_blank(), axis.title.x = element_blank())

p5 <- ggplot(dat[dat$sample.type == "EOF",], aes(Date, TSS.mgl))+
  geom_point()+
  stat_smooth(span = 0.3)+
  geom_hline(data = dat, yintercept = median(dat$TSS.mgl, na.rm= T))+
  scale_x_date(date_labels = "%m-%Y", date_breaks= "2 months")+
  rotate_x_text(angle = 45)

(p1 | p2 | p3 | p4) / p5 +
  plot_layout(guides = 'collect')+
  plot_annotation(title = 'Total Suspended Solids (milligrams / liter)',
                  caption = 'Some outliers may be omitted from visualization')
Figure 6.2

Figure 6.2

Figure 6.3

Figure 6.3

Figure 6.4

Figure 6.4

Figure 6.5

Figure 6.5

Figure 6.6

Figure 6.6

Figure 6.7

Figure 6.7

Figure 6.8

Figure 6.8

Figure 6.9

Figure 6.9

Figure 6.10

Figure 6.10

Instream concentrations across time

response = names(dat)[c(9:14,16,32,33,35)]
response = set_names(response)
scatter_fun = function (y) {
  ggplot(dat[dat$sample.type == "INST",],
         aes(x = Date, y = .data[[y]]))+
    geom_point()+
     scale_x_date(date_labels = "%m-%Y", date_breaks= "2 months")+
    rotate_x_text(angle = 45)+
    geom_smooth(span= 1)
  }

inst_plots <- map(response, ~scatter_fun(.x))
inst_plots
Figure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across timeFigure 6.11: Instream nutrient concentrations across time

Figure 6.11: Instream nutrient concentrations across time

6.2.3 Analyte by site and treatment

dats <- filter(dat, dat$sample.type == "EOF")

analyteplot <- function(analyte,Title,Ylab = "mg/L",Ylimt) {
  ggplot()+ 
    geom_boxplot(data = dats, 
                 aes(x = sampleid, 
                     y = analyte, 
                     fill= farm)
    )+
    labs(title = Title, 
         caption = "Some values may be omitted from vizualization. \n Suffix (1) is the treatment CCMT, suffix (2) is the control FBM")+
    ylab(Ylab)+
    xlab("Site")+
    coord_cartesian(ylim= c(0,Ylimt))+
    theme_bw()+
    theme(axis.text.x = element_text(angle = 45, hjust = 1),
          plot.caption = element_text(face= "italic"))
  
}


analyteplot(dats$TSS.mgl,"Total suspended solids","mg/L", 10000)
Figure 6.12

Figure 6.12

Figure 6.13

Figure 6.13

Figure 6.14

Figure 6.14

Figure 6.15

Figure 6.15

Figure 6.16

Figure 6.16

Figure 6.17

Figure 6.17

Figure 6.18

Figure 6.18

Figure 6.19

Figure 6.19

Figure 6.20

Figure 6.20

Figure 6.21

Figure 6.21

Figure 6.22

Figure 6.22

Figure 6.23

Figure 6.23

Figure 6.24

Figure 6.24

6.3 Reduction Potential Distributions

Here we can evaluate the distribution of reduction potentials. Each paired event produces a reduction (or increase) value for all the respective analytes. See section 4: Reduction Potential for explanation on how we produced these values. Again, (+) values represent a reduction relative to the control and (-) values represent negative reduction, i.e. an increase in concentrations on the treatment plots. The nature of the calculation allows for extremely negative numbers and a maximum reduction of 100%. (fbm - ccmt)/fbm If there was no nutrient in ccmt runnoff that would represent a 100% reduction. Conversely if the concentrations are higher on the ccmt treatment our (-) reduction can increase infinitely.

df <- list()

for(i in c(51,53,55,57,59,61,63,65,67,77,93,95)) {
  df1 <- mosaic::favstats(dat.reduct[,i])
  df1$i <- names(dat.reduct[i])
  df[[i -8]] <- df1
}
df <- do.call(
  rbind,
  df
)
df <- df[c(10,1:9)]
knitr::kable(df, caption = "Table 6.1: Statistical summary of reduction potentials from paired events only", digits = 2 ,
             col.names = c("Analyte", "min","Q1","median","Q3","max","mean","sd","n=", "NA")) %>% 
  kable_paper() %>% 
  remove_column(1)
Table 6.1: Statistical summary of reduction potentials from paired events only
Analyte min Q1 median Q3 max mean sd n= NA
TSS.mgl.per -8029.93 -9.19 35.22 58.99 99.37 -128.09 839.56 158 0
TUR.ntu.per -5295.52 1.73 36.43 62.59 98.93 -104.99 642.03 158 0
NO3.NO2.mgl.per -4604.35 -11.20 23.84 46.08 93.44 -76.33 458.47 158 0
TKN.mgl.per -2962.50 -110.96 -3.63 44.69 95.32 -97.78 324.63 158 0
TN.mgl.per -790.71 -9.23 14.35 41.07 94.64 -21.73 131.03 158 0
TIP.mgl.per -857.67 -5.02 24.24 44.50 94.81 -2.71 115.02 158 0
NH3.mgl.per -16746.15 -137.70 -26.87 36.44 92.46 -199.36 1341.05 158 0
OrthoP.mgl.per -1202.39 -95.21 -4.88 34.46 91.17 -60.65 172.17 158 0
NOx.mgl.per -23414.29 -117.26 10.76 67.92 99.77 -381.63 2178.48 158 0
in.runoff.ac.per -10688.04 -163.90 -16.30 28.84 94.88 -229.85 996.60 134 24
TN.lbac.per -11094.44 -105.49 -8.95 35.99 97.70 -214.13 1015.18 134 24
TIP.lbac.per -9860.39 -89.87 -3.09 43.18 96.18 -189.81 940.32 134 24
for (i in c(51,53,55,57,59,61,63,65,67,77,93,95)){

rd <- boxplot(dat.reduct[,i], outline= FALSE, na.rm= T, main = names(dat.reduct[i]) , ylab = "(+) represents reduction from treatment")
rdmean <- with(rd, stats[3,], names)
text(1, rdmean, paste(round(rdmean,0)), pos = 3)

}
Figure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplotsFigure 6.24: Reduction potential boxplots

Figure 6.24: Reduction potential boxplots